USRE42641E1 - Depth-resolved spectroscopic optical coherence tomography - Google Patents

Depth-resolved spectroscopic optical coherence tomography Download PDF

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USRE42641E1
USRE42641E1 US10/020,041 US2004101A USRE42641E US RE42641 E1 USRE42641 E1 US RE42641E1 US 2004101 A US2004101 A US 2004101A US RE42641 E USRE42641 E US RE42641E
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Joseph A. Izatt
Manish D. Kulkarni
Michael V. Sivak
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01JMEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28Investigating the spectrum
    • G01J3/44Raman spectrometry; Scattering spectrometry ; Fluorescence spectrometry
    • G01J3/4412Scattering spectrometry
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02001Interferometers for determining dimensional properties of, or relations between, measurement objects characterised by manipulating or generating specific radiation properties
    • G01B9/02002Frequency variation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02001Interferometers for determining dimensional properties of, or relations between, measurement objects characterised by manipulating or generating specific radiation properties
    • G01B9/02007Two or more frequencies or sources used for interferometric measurement
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02055Interferometers for determining dimensional properties of, or relations between, measurement objects characterised by error reduction techniques
    • G01B9/02062Active error reduction, i.e. varying with time
    • G01B9/02067Active error reduction, i.e. varying with time by electronic control systems, i.e. using feedback acting on optics or light
    • G01B9/02069Synchronization of light source or manipulator and detector
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02055Interferometers for determining dimensional properties of, or relations between, measurement objects characterised by error reduction techniques
    • G01B9/0207Error reduction by correction of the measurement signal based on independently determined error sources, e.g. using a reference interferometer
    • G01B9/02072Error reduction by correction of the measurement signal based on independently determined error sources, e.g. using a reference interferometer by calibration or testing of interferometer
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02083Interferometers for determining dimensional properties of, or relations between, measurement objects characterised by particular signal processing and presentation
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00Instruments as specified in the subgroups and characterised by the use of optical measuring means
    • G01B9/02Interferometers for determining dimensional properties of, or relations between, measurement objects
    • G01B9/02091Tomographic low coherence interferometers, e.g. optical coherence tomography
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B2290/00Aspects of interferometers not specifically covered by any group under G01B9/02
    • G01B2290/35Mechanical variable delay line

Abstract

A method is described for determining depth-resolved backscatter characteristics of scatterers within a sample, comprising the steps of: acquiring a plurality of sets of cross-correlation interferogram data using an interferometer having a sample arm with the sample in the sample arm, wherein the sample includes a distribution of scatterers therein, and wherein the acquiring step includes the step of altering the distribution of scatterers within the sample with respect to the sample arm for substantially each acquisition; and averaging, in the Fourier domain, the cross-correlation interferogram data, thereby revealing backscattering characteristics of the scatterers within the sample.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims priority under 35 U.S.C. 119 from Provisional Application Ser. No. 60/048,237, filed Jun. 2, 1997, the entire disclosure of which is incorporated herein by reference.

BACKGROUND

Optical imaging of a biological specimen has always been a formidable and challenging task because the complex microscopic structure of tissues causes strong scattering of the incident radiation. Strong scattering in tissue at optical wavelengths is due to particulate scattering from cellular organelles and other microscopic particles, as well as to refractive index variations arising within and between cell and tissue layers.

For over a century, conclusive diagnosis of many diseases of cellular origin (such as cancer) has been performed by the process of excisional biopsy, comprising the identification, removal, histological preparation and optical microscopic examination of suspect tissue samples. Many developments have taken place to aid the pathologist in interpretation of histological microstructure, primarily the development of a wide variety of histochemical stains specific to the biochemistry of tissue microstructures. This technique provides sufficient resolution to visualize individual cells within the framework of the surrounding gross tissue structure. In the last several years, a revolution has been stimulated in the field of ultra-high resolution microscopy for biomedical applications. Ultra-high resolution microscopy allows visualization of sub-cellular and sub-nuclear structures. This has resulted in the invention of tools for high resolution optical imaging, including near field scanning microscopy, standing wave fluorescence microscopy, and digital deconvolution microscopy.

These technologies are primarily designed for imaging features at or near the surface of materials. Inhomogeneties of the refractive indices inside a biological specimen leading to multiple scattering limit the probing depth of these techniques. Thus, considerable effort is required to cut and preserve the samples in order to prepare the specimen to the requirements of the microscope. In medical applications, this means that suspect tissue sites identified using minimally invasive diagnostic technologies such as endoscopy must still be acquired and processed via routine histological examination. This step introduces significant delay and expense.

The invention of confocal microscopy and its advanced development in the past few years have provided the researcher the capability to study biological specimens including living organisms without the need for tissue resection and histological processing. However, the presence of multiple scattering in samples limits confocal microscopy to specimens which are thin and mostly transparent. There is a need, therefore, for new optical methods capable of in vivo imaging deeper inside highly scattering tissues and other biological specimens.

Optical coherence tomography (“OCT”) is a technology that allows for noninvasive, cross-sectional optical imaging in biological media with high spatial resolution and high sensitivity. OCT is an extension of low coherence or white-light interferometry, in which a low temporal coherence light source is utilized to obtain precise localization of reflections internal to a probed structure along an optic axis (i.e., as a function of depth into the sample). In OCT, this technique is extended to enable scanning of the probe beam in a direction perpendicular to the optical axis, building up a two-dimensional reflectivity data set, used to create a cross-sectional, gray-scale or false-color image of internal tissue backscatter.

Many studies have suggested the use of elastic backscatter or reflectance as a noninvasive diagnostic tool for early detection of several human diseases, including cancer. The use of backscattered light is based on the fact that many tissue pathologies are accompanied by architectural changes at the cellular and sub-cellular level, for example the increase in the nuclear to cytoplasmic volume ratio accompanying neoplastic conversion. In the near infra-red (NIR) zone, the elastic scattering properties of the tissue are most strongly affected by changes in tissue features whose dimensions are on the same order as the NIR wavelength. Preliminary success in diagnosing cancer in the bladder, skin, and gastrointestinal tissues has been reported with techniques based on elastic backscatter spectroscopy. However, currently implemented spectroscopic systems do not incorporate depth resolution and thus cannot provide information on the degree of infiltration or cancer staging. Although elastic backscatter spectra can be collected with confocal techniques, the turbidity of biological samples in combination with the point spread function of confocal microscopes limit the penetration depth for acquiring spatially selective spectra to no greater than a few hundred micrometers in most tissues. Many tissue samples have features of interest located at a depth more than that can be probed by confocal techniques, but less than that of other sub-surface imaging modalities such as ultrasound. Accordingly, there is a need for a spectroscopy system that is capable of obtaining depth-resolved elastic backscatter spectra from a sample.

Inelastic scattering processes including fluorescence and Raman spectroscopy have also been exploited for noninvasive disease diagnosis. Unlike elastic scattering events, in which the incident and scattered radiation are at the same frequency, in inelastic scattering events all or part of the incident optical energy is temporarily absorbed by the atoms and/or molecules of the subject tissue, before being remitted at a different (usually lower) optical frequency. Thus, inelastic scattering processes serve as intimate probes of tissue biochemistry. Several studies have reported on laser-induced fluorescence spectroscopy as a potential early cancer diagnostic in the skin, breast, respiratory, gastrointestinal, and urogential tracts. Additional studies have reported on the more biochemically specific Raman spectroscopy for characterization of atherosclerotic lesions in the coronary arteries, as well as for early cancer detection in the gastrointestinal tract and cervix. In all studies of fluorescence, Raman, and other inelastic scattering spectroscopies in human tissues to date, means have not been available to resolve the depth of the scattered signal with micrometer-scale resolution. There is thus a need for a spectroscopy system capable of obtaining depth-resolved inelastic backscatter spectra as well as elastic backscatter spectra from a sample, such as could be obtained by extending Optical Coherence Tomography to detect inelastically scattered light. The depth resolved elastic and inelastic backscattering spectroscopic information could aid in the detection of the shapes and sizes of lesions in an affected organ and could thus assist in accurate staging of diseases such as cancer.

The inelastic scattering spectroscopies based on spontaneous fluorescence and spontaneous Raman scattering which have been used in medical diagnostic applications to date are not suitable for combination with Optical Coherence Tomography because they are incoherent scattering processes, and thus the scattered light would not be detected with OCT. However, coherent inelastic scattering processes do exist, in particular the process of stimulated emission is the coherent analog of spontaneous emission, and stimulated Raman scattering is the coherence analog of spontaneous Raman scattering. Other stimulated coherent scattering processes also occur which may find future application in medical diagnostics, for example coherent anti-Stokes Raman scattering (CARS) and four-wave mixing (FWM). All of these coherent inelastic scattering processes require the presence of pump energy which is converted into signal energy in a coherent gain process. Thus, by virtue of their coherence, stimulated coherent gain processes are suitable for combination with Optical Coherence Tomography to allow for depth resolution of the location of the inelastic scattering events. Therefore, there exists a need for a system which allows for this combination.

SUMMARY

The present invention provides a technique for depth-resolved coherent backscatter spectroscopy. This technique is an extension of OCT technology. U.S. patent application Ser. No. 09/040,128, filed Mar. 17, 1998, the disclosure of which is incorporated herein by reference, describes an improved OCT system that utilizes a transfer function model, where the impulse response is interpreted as a description of actual locations of reflecting and scattering sites within the tissue. Estimation of the impulse response provides the true axial complex reflectivity profile of the sample with the equivalent of femtosecond ranging resolution. An interferogram obtained having the sample replaced with a mirror, is the auto-correlation function of the source optical waveform. The interferogram obtained with the tissue in the sample is the measured output of the system and is known as the cross-correlation function. By deconvolving an impulse response profile from the output interferometric signal, a more accurate description of the tissue sample is obtained.

This model assists in calculating the spectral characteristics of optical elements over the bandwidth of the source by analysis of the interference resulting from internal tissue reflections. This model may also be extended to spectrally analyze light backscattered from particles in turbid media. Because individual scatterers in a turbid specimen may be considered as being essentially randomly distributed in space, the ensemble average of transfer functions obtained from cross-correlation data windowed to a specific region within the sample reveals the backscattering characteristics of the scatterers localized to that region. From this model, it is determined that the squared magnitude of the frequency domain transfer function correlates with the backscatter spectrum of scatterers.

Accordingly, the present invention provides a system or method for determining depth resolved backscatter characteristics of scatterers within a sample which includes the means for, or step of averaging (in the Fourier domain) the interferogram data obtained over a region of the sample.

In one embodiment of the present invention, the system or method includes the means for, or steps of: (a) acquiring auto-correlation interferogram data from the Low-Coherence interferometer; (b) acquiring multiple sets of cross-correlation interferogram data from the Low-Coherence interferometer having the sample under analysis in the sample arm, where the distribution of scatterers within the sample has been altered for each acquisition (e.g., by squeezing or stretching the tissue sample) or where the sample arm is repositioned slightly for each acquisition; (c) obtaining an auto-power spectrum by performing a Fourier transform on auto-correlation data; (d) obtaining a cross-power spectrum for the windowed portion of each cross-correlation data by performing a Fourier transform on the windowed portion of each cross-correlation data set; (e) obtaining a transfer function from the ratio of each cross-power spectrum to the auto-power spectrum; (f) squaring each transfer function obtained in step (e) and (g) averaging the magnitude of the squared transfer functions to reveal backscattering characteristics of scatterers resident within that window.

Based upon the model described above, any form of coherent spectroscopy can be performed in a depth-resolved manner. Accordingly, the present invention also provides a system and method for performing stimulated-emission spectroscopic optical coherence tomography (SE-SPOCT). Such a system or method includes the means for, or steps of directing an intense pump laser at the appropriate frequency to induce depth- and frequency-dependent gain in the sample volume interrogated. The depth resolved spectrum obtained according to the steps discussed above will thus contain features corresponding to the frequency-dependent round-trip gain experienced by the OCT source radiation (inelastic backscattering characteristics of the scatterers resident within the window). In a detailed embodiment of SE-SPOCT, the pump laser is cycled on and off and gated detection is performed to separate the elastic backscattering characteristics from the inelastic backscattering characteristics. Additionally, the pump laser may be modulated at a certain frequency and gated detection is performed to separate the elastic backscattering characteristics from the inelastic backscattering characteristics.

Similar to SE-SPOCT, the present invention also provides a system or method for performing stimulated Raman scattering spectroscopic OCT (SRS-SPOCT). In this embodiment, the system or method includes the means for, or the step of directing a high intensity pump light into the sample interaction region. The depth resolved spectrum obtained according to the steps discussed above will thus contain localized peaks in the depth-resolved backscatter spectrum that provide substantial vibrational/rotational spectral information of the scatterers within the sample.

Accordingly, it is an object of the present invention to provide a system and method for acquiring depth-resolved backscatter spectra of a sample, utilizing OCT. It is a further object of the present invention to provide a system and method for performing stimulated-emission spectroscopic OCT. And it is a further objective of the present invention to provide a system or method for performing stimulated Raman scattering spectroscopic OCT. These and other objects and advantages of the present invention will be apparent from the following description, the attached drawings and the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block-diagram representation of a conventional Michelson interferometer;

FIG. 2 is an interferogram of a cover slip placed on a piece of paper taken by the Michelson interferometer of FIG. 1;

FIG. 3a is a flow-diagram representing a method of the present invention;

FIG. 3b is a flow-diagram representing a method of the present invention;

FIGS. 4a-b is a flow-diagram representing a method of the present invention;

FIG. 5 is a schematic, block-diagram representation of an OCT data acquisition and digital signal processing system of the present invention;

FIG. 6 illustrates experimental results of a method of the present invention;

FIG. 7 is a schematic flow-diagram representing an alternate embodiment for obtaining a cross-power spectrum according to the present invention;

FIG. 8 is a schematic flow-diagram representing another alternate embodiment for obtaining a cross-power spectrum according to the present invention;

FIG. 9 is a schematic flow-diagram representing yet another alternate embodiment for obtaining a cross-power spectrum according to the present invention;

FIG. 10a is a flow-diagram representing a method for obtaining a spectrum of light in the sample arm according to the present invention;

FIG. 10b is a flow-diagram representation of an alternate method for obtaining a spectrum of light in the sample arm according to the present invention;

FIG. 11a is a schematic block diagram representation of an alternate data acquisition and signal processing system of the present invention;

FIG. 11b is a schematic block diagram representation of an alternate data acquisition and signal processing system of the present invention;

FIG. 11c illustrates a modification of the systems of FIGS. 11a and 11b;

FIGS. 12a-e is a schematic block diagram representation of an alternate data acquisition and signal processing system of the present invention, including example diagrams representing signals obtained by the system;

FIG. 13 is an illustration of the operation of the alternate embodiments of FIGS. 11a, 11b, and 12a;

FIG. 14a is a schematic block diagram representation of a system for gated or synchronous detectection for use with the embodiments of FIGS. 11a, 11b, and 12a;

FIG. 14b is timing diagram representing the operation of the system of FIG. 14a;

FIG. 15a is a schematic block diagram representation of another system for gated or synchronous detection for use with the embodiments of FIGS. 11a, 11b, and 12a; and

FIG. 15b is a timing diagram representing the operation of the system of FIG. 15a.

DETAILED DESCRIPTION

I. Michelson Interferometer

As shown in FIG. 1, a conventional scanning Michelson interferometer can be utilized to obtain the depth resolved measurements of reflectors and scatterers in a sample. A low coherence light source 10 is separated into two beams by a 50/50 beam splitter 16, fifty percent of the light power is transmitted to a sample arm 12 and the remaining fifty percent is directed to a reference arm 14. The sample arm 12 includes a sample probe 18, which focuses the sample beam into the sample 20 and collects the retroreflected light from the sample. The reference arm 14 includes a reference probe 22 which transmits the reference beam onto a retroreflecting mirror 24, translating towards or away from the reference probe, and collects the light retroreflected back from the mirror 24. The retroreflected beams from the sample 20 and mirror 24 are combined again in the beam splitter 16 into a detected electric field 26, which is directed to the optical detector 28. Because a low coherence light source 10 is used, an interferometric signal is produced at the detector 28 when the sample probe path distance to a reflecting or scattering site within the sample 20 matches the reference arm length, to within a source coherence length. For every reflecting or scattering site within the sample, a fringe pattern will appear in the interferometric signal similar to that as shown in FIG. 2. The axial profiles of backscatter versus depth are measured by translating the reference mirror 24 and by synchronously recording the envelope of the interferometric signal at the detector 28. This profile is known as the OCT A-scan of the sample. Two dimensional cross-sectional imaging of the sample is performed by laterally scanning the sample probe 18 during successive A-scans. The resulting data set is processed in a computer 30 and displayed as a gray scale or false color image. A series of two-dimensional images can be acquired by scanning the probe beam perpendicular to the direction of lateral scanning. The series of two-dimensional images can then be rendered into a three dimensional display or a pseudo three dimensional display in gray scale or false color.

Those of ordinary skill in the art will recognize that, although it is preferred to scan the sample probe 18 with respect to the sample 20, the sample may also be scanned with respect to a stationary sample probe. It also to be understood, that for the purposes of this disclosure, the term “optical” is to pertain to all ranges of electromagnetic radiation, and preferably pertains to the range of 100 nanometers to 30,000 nanometers.

In developing the present invention, a unique transfer function model has been developed for OCT interaction with the sample, where the impulse response is interpreted as a description of the actual locations of the reflecting and scattering sites within the sample. Based upon this model, the transfer function of the system can be calculated from the source auto-power spectrum and the cross-power spectrum of the electric fields in the reference and sample arms. The estimation of the impulse response from the transfer function provides the true axial complex reflectivity profile of the sample with the equivalent of femtosecond temporal resolution. Extending this model, it is determined that the squared magnitude of the frequency domain transfer function correlates with the backscatter spectrum of scatterers within the sample. In particular, because individual scatterers in a turbid specimen are randomly distributed in space, the ensemble average of transfer functions obtained from cross-correlation data windowed to a specific region within the sample reveals the backscattering characteristics of the scatterers localized to that region.

II. Model for Low Coherence Interferometry in Thick Scattering Media

The present invention is based on a systems theory model which treats the interaction of the low coherence interferometer with the specimen as a linear shift invariant (LSI) system. For the scan lengths of a few mm, typical of OCT imaging, it is assumed that group velocity dispersion is negligible and the group and phase velocities are equal. In the NIR region absorption causes negligible attenuation as compared to the attenuation due to multiple scattering within tissues. This model does not take into account the attenuation of light due to multiple scattering as well as absorption.

An optical wave with an electric field with space and time dependence expressed in scalar form as 2{tilde over (e)}i(t, z) is assumed to be incident on a Michelson interferometer, as illustrated in FIG. 1. An arbitrary scaling factor of 2 has been introduced for the sake of convenience. The electric field can be expressed as 2{tilde over (e)}i(t, z)=2e0i(t, z)cos(2 πf0t−k0z+φ(t,z)) where f0 is the central frequency of the source spectrum and k0(=2p/l0) is the corresponding wave number. l0 is the corresponding center wavelength. Here t and z indicate the time and distance traveled by the wave, respectively. 2e0i(t, z) and φ(z,t) are the time and space dependent amplitude and phase of the wave. The analytic signal representation of this electric field is given by 2e0i(t, z)exp[j(2 πf0t−k0z+φ(t, z))] where j=√(−1). In most cases we will use this complex analytic representation to denote even those quantities that are real for simplicity. The quantity 2ei(t, z)=2e0i(t, z)exp [jφ(t, z)] is known as the complex envelope of the signal. We can write the term 2pf0 t−k0 z as k0(vt−z) where v is the group velocity at the source center frequency. Here we assume that the group and phase velocities are equal. We assume that the complex envelope is varying much slowly on the scale of the source wavelength. We further require the complex envelope to be a function of (vt−z). Thus it is denoted by 2ei(vt−z)=2e0i(vt−z)exp[jφ(vt−z)]. All the temporal dependence is expressed in terms of a path delay and thus electric fields can be treated as pure functions of space. Apart from the center frequency, all the information about the wave can be derived from this complex envelope. Therefore we will use the term electric field to denote the field {tilde over (e)} itself as well as its complex envelope e. In the case when the group and phase velocities are unequal, {tilde over (e)}(vt−z)=2e0i(vt−z)exp[jφ(vt−z)]exp(jk0(ct−z)), where c is the phase velocity. This analysis will still be applicable. At the 50/50 beamsplitter, half the power gets coupled into the reference arm and the rest into the sample arm. Since the power is proportional to the square of the electric field, the electric field at the beam splitter in the reference arm is given by √2ei(vt), setting z=0 at the beamsplitter. The lightwave reaching the reference mirror assumes the form √2ei(vt−lr), where lr and ls are the optical path lengths in the reference and sample arms, respectively. If the mirror is ideal, it will reflect back the same electric field. Then the field returning to the beam splitter is indicated as √2ei(vt−2lr). √2ei(vt−ls) is the field reaching the sample. In the sample arm, the light interacts with the specimen and the backscattered field is given by √2es(vt−ls). The backscattered field reaching the beam splitter takes the form √2es(vt−2ls).

The fields returning from the reference and sample arms again get separated 50/50 into the arms consisting of the source and detector. Therefore the interference of {tilde over (e)}i(vt−2lr) and {tilde over (e)}s (vt−2ls) is incident on the detector. The reference arm length can be varied by various means. One such method is mechanically scanning the reference mirror causing sweeping of the reference arm length lr. Since the detector response time (e.g., nanosecond to microsecond for typical optical receivers) is much longer than the optical wave period (˜10−15 second) the photocurrent generated by a square law detector is proportional to
ĩd˜{tilde over (R)}is(Δl)=<{tilde over (e)}i(vt){tilde over (e)}s*(vt+Δl)>  (a1)
The superscript * indicates a complex conjugate. An interferogram obtained having the sample replaced with a mirror in the sample arm, is the “auto-correlation function” {tilde over (R)}ii(Δl). The tissue is modeled as an LSI system. The “auto-correlation function” {tilde over (R)}ii(Δl) of the source optical wave form is treated as an input to the LSI system. The interferogram obtained with the sample in the sample arm is the measured output of the LSI system, known as the “cross-correlation function” {tilde over (R)}is(Δl). The cross- and auto-correlation functions are expressed as:
{tilde over (R)}is(Δl)=<{tilde over (e)}i(vt){tilde over (e)}s*(vt+αl)>, {tilde over (R)}ii(Δl)=>{tilde over (e)}i(vt){tilde over (e)}i*(vt+Δl)>  (a2)

Note that {tilde over (R)}ii(Δl), and {tilde over (R)}is(Δl) are the complex analytic representations of the signals measured, i.e., only the real parts of {tilde over (R)}ii(Δl), and {tilde over (R)}is(Δl) are actually measured.

We represent the optical field interaction with the LSI sample as a transfer function {tilde over (H)}(k) (where k is wavenumber) whose inverse Fourier transform is the impulse response {tilde over (h)}(z):
{tilde over (e)}s(−Z)={tilde over (e)}i(−z)

Figure USRE042641-20110823-P00001
{tilde over (h)}*(z)   (b)
where
Figure USRE042641-20110823-P00001
represents convolution. Note that shift invariance allows omission of the terms vt in this expression. The convolution theorem leads to
{tilde over (E)}s(k)={tilde over (E)}i(k){tilde over (H)}*(k)   (c)
where {tilde over (E)}s(k), {tilde over (E)}i(k), and {tilde over (H)}(k) are the Fourier transforms of {tilde over (e)}s(z), {tilde over (e)}i(z), and {tilde over (h)}(z), respectively. {tilde over (H)}(k) is the system transfer function. The LSI assumption provides:
{tilde over (e)}s(vt−2ls)={tilde over (e)}i(vt−2ls)
Figure USRE042641-20110823-P00001
{tilde over (h)}*(−(vt−2ls))   (d)
Inserting Eq. (d) in Eq. (a) leads to
{tilde over (R)}is(Δl)={tilde over (R)}ii(Δl)
Figure USRE042641-20110823-P00001
{tilde over (h)}(Δl), {tilde over (S)}(k)={tilde over (S)}ii(k){tilde over (H)}(k)   (e)
Figure USRE042641-20110823-P00002
{tilde over (H)}(k)={tilde over (S)}is(k){tilde over (S)}ii(k)   (f)

Note that according to the Wiener-Khinchin theorem, Fourier transforming the autocorrelation and cross-correlation functions gives us {tilde over (S)}is(k) and {tilde over (S)}ii(k), respectively. {tilde over (S)}is(k) and {tilde over (S)}ii(k) are the auto-power and cross-power spectral densities, respectively.

This analysis will be useful when raw interferograms are measured. It is convenient to measure the complex envelopes of the interferometric data by demodulating {tilde over (R)}ii(Δl), and {tilde over (R)}is(Δl). Such a demodulation assists in noise reduction which otherwise needs to be achieved by using a band-pass filter with sharp cutoffs. Demodulation also allows use of lower sampling frequency while digitizing the data. Rii(Dl) and Ris(Dl) are complex envelopes of {tilde over (R)}ii(Δl) and {tilde over (R)}is(Δl), respectively. Thus Rii(Dl) and Ris(Dl) will be measured after coherent demodulation. Note that |Rii(Dl)| and |Ris(Dl)| will be measured after incoherent demodulation.

Ris(Dl) is obtained by coherently demodulating {tilde over (R)}is(Δl) at the center wavenumber k0. Note that when implemented in hardware, the demodulation frequency needs to be specified in terms of the temporal frequency of the detector current. The center frequency of the detector current is

f r = V ϕ k 0 2 π
which is same as a Doppler shift frequency on the reference arm light. Vφ is the scan rate of optical phase delay. Vφ=2Vr for a simple mechanical reference mirror translator. The demodulation frequency can be chosen to be equal to fr for demodulating the detector current to obtain Ris(Dl) and Rii(Dl).

Therefore let's analyze the system using complex envelopes of the electric fields and the impulse response. We represent the optical field complex envelope interaction with the LSI sample as a transfer function H(k) (where k is wavenumber) whose inverse Fourier transform is the impulse response h(z):
√2es(z)=√2ei(z)

Figure USRE042641-20110823-P00001
h*(−z) and √2Es(k)=√2Ei(k)H*(k)   (1a)
where
Figure USRE042641-20110823-P00001
represents the convolution operation. Es(k) and Ei(k) are Fourier transforms of es(z) and ei(z), respectively. Note that {tilde over (h)}(vt−z)=h(vt−z)exp[j(k0(vt−z)] and {tilde over (H)}(k)=H(k+k0). Also the LSI assumption leads to
√2es(vt−ls)=√2ei(vt−ls)
Figure USRE042641-20110823-P00001
h(−(vt−ls)).   (1b)
The fields returning from the reference and sample arms again get separated 50/50 into the arms consisting of the source and detector. Therefore the interference of {tilde over (e)}i (vt−2lr) and {tilde over (e)}s (vt−2ls) is incident on the detector. The reference arm length can be varied by various means. One such method is mechanically scanning the reference mirror causing sweeping of the reference arm length lr. Since the detector response time (e.g., nanosecond to microsecond for typical optical receivers) is much longer than the optical wave period (˜10−15 second) the complex envelope of the photocurrent generated by a square law detector is proportional to
iD˜<[ei(vt−2lr)+es(vt−2ls)][ei(vt−2ls)+esvt−2ls)]*>, =<[ei(vt)+es(vt+Dl)][ei(vt)+es(vt+Dl)]*>,  (2)
where <> denotes integrating over the detector response time which is long compared to the electric field period, and 2(ls−lr)=Dl is the round trip optical path length difference. When the reference arm length is scanned at a constant velocity, after filtering out the dc components, the time varying components of Eq. 2 reduce to
iD˜Ris(Δl)=<ei(vt)es(+Δl)>  (3)
which is just the cross-correlation between the complex envelopes of the fields returning from the reference and sample aims. iD is the complex envelope of the corresponding current at the photoreceiver output. We can also obtain the autocorrelation function of the source field Rii(Dl) by performing the same operation with a mirror in the sample arm, in which case h(z)=d(z) and es(z)=ei(z)
Figure USRE042641-20110823-P00002
Rii(Δl)=<ei(vt)ei*(vt)+Δl)>. For an optical source with a well characterized spectrum, the form of the autocorrelation function Rii(Dl) is calculated explicitly by computing the inverse Fourier transform of the power spectral density. For a superluminescent diode source approximated by a Gaussian power spectrum, we obtain

Real  part  of R ~ LL ( Δl ) e 0 l 2 exp [ - ( Δl l c ) 2 ln 2 ] · cos ( k 0 Dl ) ; ( 4 ) l c = 4 ( ln 2 ) / ( Dk )
where k0 is the central wavenumber of the source and Dk is the FWHM spectral width. The envelope of the detected signal (plotted as a function of (ls−lr)) from a reflection in the sample arm is a Gaussian function centered at zero reference arm delay and with a FWHM width equal to the coherence length lc. Substituting Eq. 1 in Eq. 3 results in
Ris(Dl)=Rii(Dl)

Figure USRE042641-20110823-P00001
h(Dl).   (5)
According to the Wiener-Khinchin theorem, Fourier transforming the autocorrelation and cross-correlation functions gives us Sii(k) and Sis(k). Sii(k) and Sis(k) are the auto-power and cross-power spectral densities, respectively. We form an estimate of the transfer function H(k) in an arbitrary turbid sample which may contain many closely spaced reflections by Fourier transforming both sides of Eq. 5:
Sis(k)=Sii(k)H(k), H(k)=Sis(k)/Sii(k), h(z)
Figure USRE042641-20110823-P00003
H(k)   (6)
where a Fourier transform pair is related by
Figure USRE042641-20110823-P00004
.

In practice, the correlation functions defined in Eq. a1, a2 and 3 are hard to measure. The measured (or estimated) correlation functions are influenced by the properties of the optical elements, the measurement electronics, and data acquisition systems, and various noise sources. Therefore what we measure are “estimates” of {tilde over (R)}ii (Δl)(or Rii(Δl)) and {tilde over (R)}is(Δl)(or Ris(Δl)). However, for the description of depth resolved spectroscopy systems and claims we will still use the symbols {tilde over (R)}ii(Δl)(or Rii(Δl)) and {tilde over (R)}is(Δl)(or Ris(Δl)) to indicate the “estimates” of auto-correlation and cross-correlation functions, respectively. For the purposes of clarity, the terms “auto-correlation and cross-correlation functions” may be used for the terms, “the estimates of auto-correlation and cross-correlation functions” in describing the present inventions.

Similarly the measured (or estimated) power spectra are influenced by the properties of the optical elements, the measurement electronics, and data acquisition systems, and various noise sources. Therefore what we measure are “estimates” of {tilde over (S)}ii(k) (or Sii(k)) and {tilde over (S)}is(k) (or Sis(k)). However, for the description of spectroscopy algorithms and claims we will still use the symbols {tilde over (S)}ii(k) (or Sii(k)) and {tilde over (S)}is(k) (or Sis(k)), to indicate the “estimates” of auto-power and cross-power spectra, respectively. For the purposes of clarity, the terms “auto-power and cross-power spectra” may be used for the terms, “the estimates of auto-power and cross-power spectra” in describing the present inventions.

While we describe the specific case of a device which uses infra-red light source, the spectroscopy procedure is applicable to any interferometric device illuminated by any electromagnetic radiation source.

In Eqs. b, c, 1a, 1b, and 5 we describe the light-specimen interaction as a linear shift invariant system. We describe the deconvolution methods based on Eqs. e,f, and 6. It should be apparent to a person skilled in the art that the interaction described by Eqs. b, c, e,f, 1a, 1b, 5, and 6 can be exploited by many other methods in space/time domain as well as frequency domain including iterative deconvolution methods, etc. This model also forms the basis of “blind” deconvolution methods which do not use a priori information about the auto-correlation function but assume that it convolves with the impulse response.

The true transfer function H(k) is rarely estimated or measured. In most practical cases, what we get is an “estimate” of the transfer function which is different than the true transfer function. One can obtain this estimate in various ways. One such method is taking the ratio of cross-power spectrum and the auto-power spectrum and taking the complex conjugate of the ratio.

Next we interpret the impulse response h(z) and the transfer function H(k). All information regarding the spatially varying and frequency dependent complex reflectivity of the sample is contained in the space domain function h(z). The interpretation for deconvolution is an approximation of that for spectroscopy. In the case of deconvolution, we model tissue as a body having several layers of materials possessing different refractive indices. The impulse response can be interpreted as a description of the actual locations and reflectivities of reflecting sites within the sample arising from index of refraction inhomogeneities. The impulse response takes a form of a series of spikes (i.e., delta functions) which are located at the reflection sites while dealing with discrete data. These spikes have heights equal to the electric field reflectivities at these sites within the tissue. This information is available over a length L within the tissue where L is the reference mirror scan length.

In order to describe the impulse response quantitatively, it is convenient to deal with discrete representations of the impulse response and crosscorrelation function. It will also be helpful to do so since we measure quantized values of the discrete representations of cross-correlation functions using a computer. We assume that M samples of Ris(Dl) are acquired over a length L. Suppose Δz is the sampling interval. The numbers
Ris(1), Ris(2), . . . , Ris(n), . . . , Ris(M)
denote M measurements of a cross-correlation function sampled at distances Δz, 2Δz, 3Δz, . . . This implies that
Ris(n)=Rii(n)

Figure USRE042641-20110823-P00001
h/(n).   (7)
Rii(n) and h(n) are discrete representations of the autocorrelation function and the target impulse response, respectively. Now, as discussed earlier, h(n) assumes a form of a series of spikes (i.e., discrete delta functions) which are located at the reflection sites. In a tissue sample, one usually does not find a reflection site at every sample. Therefore the probability of occurrence of an interface at a sample is much less than one. A random sequence of zeros and ones is known as a Bernoulli sequence. If the adjacent elements in such a sequence are completely unrelated, then such a sequence is known as a white sequence (since the power spectrum of such a sequence is white). We could possibly represent the impulse response by a Bernoulli event sequence b(n). The sequence provides a one every time an interface occurs and a zero in the absence of a reflector at the sample point. However, the amplitude of the reflectivity is not constant and fluctuates randomly due to refractive index inhomogeneities and hence we need to multiply this sequence by a Gaussian random number generator g(n), g(n) is also a white sequence. Therefore
h(n)=b(n)g(n).   (8)
This essentially means that when at every point in b(n) a one occurs (i.e., a reflection site occurs), we turn on our Gaussian random number generator and replace the one by the output of the generator. The value of this random number represents the reflectivity at that point. If the reflectivities are complex, one can generate a complex Gaussian random number. We are assuming that all reflections occur at the interfaces and the effects of point scatterers do not interfere with the process of impulse response estimation.

In order to perform spatially resolved spectroscopy, a more complicated interpretation of the transfer function is required. For a monochromatic wave with an amplitude of one and zero initial phase incident on a reflector, the reflected field {tilde over (e)}s is related to the incident field by the relation,
{tilde over (e)}i=exp [jk(vt−z)], {tilde over (e)}s={tilde over (H)}(k){tilde over (e)}i={tilde over (H)}(k) exp [jk(vt−z)]  (9)
where {tilde over (H)}(k) is the reflection coefficient (i.e., backscattering coefficient) at a wavenumber k. {tilde over (H)}(k) is real for many particles. Then |{tilde over (H)}(k)|2 is the intensity reflectivity (i.e., backscattering cross-section) at a wavenumber k. If a monochromatic beam of light is incident on a group of identical particles located at the same depth, the effective {tilde over (H)}(k) would just get scaled by the number of scatterers due to coherent addition of the scattered waves. However, if they are situated at different depths, then the reflections from all the scatterers would add coherently (i.e., interfere) and the impulse response would be complex because of phase delays occurred due to different depths of the particles. Therefore the effective {tilde over (H)}(k) would also be complex. A similar phenomenon would occur if the particles were dissimilar from each other. In both cases |{tilde over (H)}(k)|2 would represent effective backscattering cross-section of the scatterers at a wavenumber k. We prove that |{tilde over (H)}(k)|2 is related to the weighted average of the reflectivities of heterogeneous scatterers. If a low-coherence light source is used, the reflections from only those scatterers located within a few coherence lengths would add coherently. In that case |{tilde over (H)}(k)|2 relates to the weighted average of the backscatter spectra of these non-homogenous scatterers.

Let us examine the complex envelope h(n) quantitatively. For a homogeneous medium, we can write
h(n)=b(n)

Figure USRE042641-20110823-P00001
c(n)   (10)
where b(n) is a Bernoulli sequence as discussed earlier and c(n) is the inverse Fourier transform of C(k). C(k) denotes spectrally dependent electric field backscattering coefficient of the scatterers. We call c(n) as the specific impulse response of a single scatterer. Thus the frequency dependent backscattering cross-section of particles is represented by |C(k)|2. The Fourier transform of b(n) is given by B(k) and E{|B(k)|2} represents the expectation value (i.e., the statistical average) of |B(k)|2 and is equivalent to the power spectral density of the Bernoulli sequence. For a white sequence, this can be assumed to be equal to a constant (in this case can be assumed to be 1 for simplicity) for all wavenumbers. Fourier transforming both sides of Eq. 10 provides
{tilde over (H)}(k)=B(k)C(k).   (11)
Taking magnitude square of both sides gives,
|{tilde over (H)}(k)|2=|B(k)|2|C(k)|2.   (12)
Obtaining ensemble averages on both sides yields,
E{|{tilde over (H)}(k)|2}=E{|B(k)|2|C(k)|2}.   (13)
Since C(k) is not a randomly varying function, we get
E{|H(k)|2}=E{|B(k)|2}|C(k)|2=1+|C(k)|2=C(k)|2.   (14)

Thus averaging several measurements of |H(k)|2 over a volume cell of interest can provide the backscatter spectrum of the individual particles localized within the homogeneous medium. While computing the spectra of scatterers located deep inside a specimen, one should note that C(k) has the information regarding the backscatter spectrum of scatterers as well as round-trip spectral filtering due to the intervening medium.

Now as indicated in Eq.(c), {tilde over (H)}(k) is the quantity that actually interacts with the electric field. Using
{tilde over (H)}(k)=H(k+k0) and {tilde over (C)}(k)=C(k+k0),   (14a)
E{|{tilde over (H)}(k)|2}=|{tilde over (C)}(k)|2.   (14b)

|{tilde over (C)}(k)|2 is the quantity that actually interacts with the electric field and is the actual measure of the backscatter spectrum.

In an inhomogeneous medium (such as a tissue specimen), a mixture of various particles within a few source coherence lengths can be described as
h(n)=b1(n)

Figure USRE042641-20110823-P00001
c1(n)+b2(n)
Figure USRE042641-20110823-P00001
c2(n)+b3(n)
Figure USRE042641-20110823-P00001
c3(n)   (15)
where bi(n) {i is a natural number} is a Bernoulli sequence describing positions of ith type of scatterers having the specific impulse response ci(n). Let bi(n) be white processes. Suppose these processes are statistically independent of each other. Fourier domain representation of Eq. 15 is
{tilde over (H)}(k)=B1(k)C1(k)+B2(k)C2(k)+B3(k)C3(k)+  (16)
where Bi(k) and Ci(k) are Fourier transforms of bi(n) and ci(n), respectively. Taking magnitude squares on both sides yields,

H(k) 2 = i = 1 M B i (k) 2 C i ( k ) 2 + B 1 (k)C 1 (k)B 2 * (k)C 2 * (k) + B 1 (k)C 1 (k)B 3 * (k)C 3 * (k) + ( 17 )
where M is the total number of types of scatterers. Taking expectation values on both sides,

E { H(k) 2 } = i = 1 M E { B i (k) 2 C i ( k ) 2 } + E{B 1 (k)C 1 (k)B 2 * (k)C 2 * (k) } + E { B 1 (k)C 1 (k)B 3 * (k)C 3 * (k) } + ( 18 )
Since we are dealing with white processes, the terms E {|Bi(k)|2}=Ki where Ki are constants. Now Ki's are proportional to the probabilities pi's of the occurrence of one in each Bernoulli process as long as pi's are much smaller than 0.5. Bernoulli processes can be considered white only within the bandwidth of the light source. Since the average of a Bernoulli sequence is non-zero and equals to pi, there is a spike at zero frequency in the power spectrum and theoretically this process is not white. However, since our measurements are limited to the bandwidth of the source, we model these processes as white. When pi's are small, an increase in pi implies an increase in number of scatterers and hence stronger echoes are obtained. Since there are more zeros than ones, all the higher frequencies have equal strength and the strength increases with an increase in pi. In the power spectrum, the splice at dc does not increase significantly. Therefore Ki increases. When pi's are close to 0.5 or higher, there are many ones occurring and they may occur next to each other. That would imply the presence of a scatterer at every sample, which is rare and unlikely, and in such a case, we should be sampling more often. Also, even if the reflections are stronger, most of the power is in the dc level spike and an increase in pi's simply implies stronger spikes at dc.

The lower row on the right hand side of Eq. 18 can be written as

M i , j = 1 E{B i T ( k ) C i (k)B 1 * ( k ) C 1 * (k)} ( 19 )
Since bi(n) are statistically independent of each other, so do Bi(k) and B*l(k) and we get

M i , j = 1 E { B i ( k ) } E B i * ( k ) C i ( k ) C i * ( k ) ( 20 )
Now Bi(k) is a Fourier transform of bi(n):

B i ( k ) = m = - b i ( n ) exp { - j 2 πkn } . ( 21 )
This implies that

E { B i ( k ) } = m = - E { b i ( n ) } exp { - j 2 πkn } = p l m = - exp { - j2πkn } = p l δ ( k ) . ( 22 )
Therefore the cross terms become

M i , j = 1 p i p j C l ( 0 ) C i ( 0 ) ( 23 )
considering the fact that δ(k) is just a spike of height one at k=0 in the case of a discrete Fourier transform. Clearly, these terms are not measurable for we can measure the spectra only within the bandwidth of the source and hence we can rewrite Eq. 18 as

E { H ( k ) 2 } = M i = 1 K i C i ( k ) 2 } ( 24 )
which is same as the weighted average of the spectra of different scatterers situated within a few coherence lengths. Since the coherence length of the source is short, the depth over which the spectral information is obtained can be controlled by limiting the reference arm scan to a region of interest within the sample, or alternatively by digitally windowing the region of interest from one or more fill length reference arm scans. Thus the transfer function H(k) obtained over a wide range of path differences contains all available information concerning interaction of the tissue specimen with the sample arm light, including modifications in both amplitude and phase.

Again as indicated in Eq.(c), {tilde over (H)}(k) is the quantity that actually interacts with the electric field. Using {tilde over (H)}(k)=H(k+k0) and {tilde over (C)}i(k)=Ci(k+k0),

E { H ~ ( k ) 2 } = i = 1 M K i C ~ i ( k ) 2 } ( 24 a )

In summary, for a monochromatic wave incident on a reflector, {tilde over (H)}(k) is the reflection coefficient (i.e., backscattering coefficient) at a wavenumber k. {tilde over (H)}(k) is real for many particles. |{tilde over (H)}(k)|2 is the intensity reflectivity (i.e., backscattering cross-section) at a wavenumber k. If a monochromatic beam of light is incident on a group of identical particles located at the same depth, the effective {tilde over (H)}(k) would just get scaled by the number of scatterers due to coherent addition of the scattered waves. However, if they are situated at different depths, then the reflections from all the scatterers would add coherently and h(z) would be complex because of phase delays occurred due to different optical depths of the particles. Therefore the effective H(k) would also be complex. Thus |{tilde over (H)}(k)|2 would be related to the effective backscattering cross-section of scatterers at a wavenumber k. If a low-coherence light source is used, the reflections from scatterers located within the coherence length would add coherently. In that case |{tilde over (H)}(k)|2 would be related to the effective backscatter spectrum of scatterers.

The impulse response h(z) essentially is a convolution of two functions, viz., a function b(z) which describes locations of scatterers and a function c(z) which is the inverse Fourier transform of C(k). C(k) denotes spectrally dependent electric field backscattering coefficient of the scatterers. The wavenumber dependent backscattering cross-section of the particles is represented by |C(k)|2. We label c(z) as the specific impulse response of scatterers. While dealing with discrete data, h(z) is represented by h(n). For a homogeneous medium, we can write h(n)=b(n)

Figure USRE042641-20110823-P00001
c(n) where b(n) and c(n) are discrete representations of b(z) and c(z), respectively. We could represent b(n) by a white Bernoulli sequence which is a series of randomly occurring zeros and ones and adjacent elements of the sequence are not related to each other. As shown in Eq. 14, above, because averaging estimates of |B(k)|2 for a white sequence is assumed to be equal to a constant (1 for simplicity), averaging estimates of |H(k)|2 (obtained from different locations in a homogeneous section of the specimen) provides an estimate of |C(k)|2 which is the elastic backscatter spectrum of scatterers residing within that homogeneous region. The short source coherence length allows to control the depth over which the spectral information needs to be measured. This is achieved by selecting the reference arm scan to an area of interest in the sample, or alternatively by windowing the area of interest from one or more full length reference arm scans. While computing the spectra of scatterers located deep inside a specimen, one should note that C(k) has the information regarding the backscatter spectrum of scatterers as well as round-trip spectral filtering due to the intervening medium. Thus the interferometric signal contains depth resolved information about both the spatial distribution of scattering centers within a tissue sample, as well as about the spectral characteristics of the individual scatterers.

The system design gets simplified if we coherently demodulate the interferometric data. C(k) would be estimated using such a system. However, |{tilde over (C)}(k)|2 or E{|{tilde over (H)}(k)|2} are preferably calculated as shown in Eq. 14b and Eq. 24a since they represent true interacting spectral characteristics of the tissue. If we process interferometric data directly, then |{tilde over (C)}(k)|2 or E{|{tilde over (H)}(k)|2} will be obtained by performing the above analysis.

The above model also allows one to measure actual spectrum of the light in the sample arm. The spectrum of light in the sample arm is defined as

Figure USRE042641-20110823-P00005
ss(k)={tilde over (E)}s(k){tilde over (E)}*s(k)
Using {tilde over (E)}s(k)={tilde over (E)}i(k){tilde over (H)}*(k) we get

S ~ ss ( k ) = S ~ ii ( k ) H ~ ( k ) 2 = S ~ is ( k ) 2 / S ~ ii ( k )
Thus the spectrum of light in the sample arm is the source power spectrum multiplied by a function which has information regarding scatterers' locations and scatterers' backscattering spectra. Since we are interested in backscattering spectra, one needs to average

Figure USRE042641-20110823-P00005
ss(k), i.e., compute E{{tilde over (E)}s(k){tilde over (E)}*s(k)}. We denote E{{tilde over (E)}s(k){tilde over (E)}*s(k)} by {tilde over (S)}ss(k), i.e., {tilde over (S)}ss(k)=E{
Figure USRE042641-20110823-P00005
ss(k)}

Thus Sss(k) is given by:

S ~ ss ( k ) = S ~ ii ( k ) E { H ~ ( k ) 2 } = { S ~ is ( k ) 2 } / S ~ ii ( k )
for a homogeneous medium,

S ~ ss ( k ) = S ~ is ( k ) E { H ~ ( k ) 2 } = S ~ ii ( k ) C ~ ( k ) 2
and for a heterogeneous medium,
{tilde over (S)}ss(k)={tilde over (S)}ii(k)Σi=1 MKi|{tilde over (C)}i(k)|2.
III. Depth Resolved Spectroscopy

Following from the above model, the present invention provides a system and method for determining depth resolved backscatter characteristics of scatterers within a sample by averaging (in the Fourier domain) the interferogram data obtained over a region of the sample. In particular, the backscatter characteristics are obtained according to the steps as illustrated in FIGS. 3a, 3b, 4a and 4b.

As shown in FIG. 3a, a first embodiment of a method for determining depth resolved backscatter characteristics of scatterers within a sample is illustrated. As indicated in step 31, the auto-correlation function {tilde over (R)}ii(Δl) over a predetermined depth D is acquired from an OCT system having an optical reflector in the sample arm; and as indicated in step 32, the auto-power spectrum {tilde over (S)}ii(k) is obtained from the auto-correlation data by performing a Fourier transform on the auto-correlation data.

As will be appreciated by those of ordinary skill in the art, there are several ways to obtain the auto-power spectrum for an OCT system, all of which are within the scope of the present invention. For example, the auto-correlation data can be measured using a strong reflector which is a part of the specimen itself; the auto-correlation function can be modeled using the information about the radiation source; and the auto-correlation function can be also calculated using the knowledge of the source power spectral density. For instance, the inverse Fourier transform of the measured source power spectrum would provide an estimate of the auto-correlation function. Additionally, since the auto-power spectrum is nothing but the source power spectrum, the auto-power spectrum can be obtained using the knowledge of the source. For instance, the source power spectrum measured using any spectrometer or a spectrum analyzer would provide an estimate of the auto-power spectrum.

As indicated in steps 33, 34, 35 and 36, multiple sets of cross-correlation data are obtained, where the distribution of scatterers within the sample has been altered for each acquisition or where the sample arm is repositioned slightly for each acquisition. As indicated in step 33 the cross-correlation function {tilde over (R)}′is(Δl) over a full length L is acquired from the OCT system having the biological tissue sample in the sample arm; next, as indicated in step 34, the cross-correlation function is segmented into short segments of length D each to obtain depth resolved spectra with axial resolution D. Length D is typically longer than or equal to the source coherence length. These segments of cross-correlation data {tilde over (R)}″is(Δl) are called {tilde over (R)}is(Δl). As indicated in step 35, it is determined whether a sufficient number of cross-correlation functions have been acquired; and as indicated in step 36, if more data is needed, the distribution of scatterers within the sample is altered or the sample arm is slightly repositioned prior to returning to step 33.

The number of sets of cross-correlation data to obtain depends upon the desired estimation accuracy of E{|{tilde over (H)}(k)|2}, and typically ranges from 50 to 500 scans. In step 36, the distribution of scatterers can be altered, for example, by lightly squeezing or stretching the tissue sample, by propagating sound or ultrasonic waves through the tissue while acquiring the data, or by repositioning the sample arm with respect to the sample. For the purposes of the present invention such steps will be referred to as altering the distribution of scatterers with respect to the sample arm.

If, in step 36, the sample arm is repositioned, the extent of such repositioning depends upon the beam diameter at the depth of interest, and is typically 20-50 mm. The separation between two adjacent scans should be at least the source beam diameter in the tissue. Since the beam waist is different at different depths within the tissue, the minimum required separation will be different for each depth.

As indicated in step 37, the cross-power spectrum {tilde over (S)}is(k) is obtained from each cross-correlation function by performing a Fourier transform on the cross-correlation function {tilde over (R)}is(Δl). As indicated in step 39, a transfer function H(k) is determined for each cross-power spectrum {tilde over (S)}is(k) by taking the ratio of each cross-power spectrum {tilde over (S)}is(k) versus the auto-power spectrum {tilde over (S)}ii(k). And as indicated in step 40, the magnitude of the backscatter spectrum C(k) is calculated by averaging the magnitudes of the squared transfer functions and then taking the square root of the average.

FIG. 3b illustrates a slightly modified version of the method illustrated in FIG. 3a. In particular, steps 33 and 34 of FIG. 3a are replaced with step 33′ in FIG. 3b. As indicated in step 33′ the cross-correlation function {tilde over (R)}′is(Δl) over a full length L is acquired; however, the full length L is equal to the desired segment length D, and therefore, a step of segmenting the cross-correlation data is not required.

FIG. 4a illustrates another embodiment of a method for determining depth resolved backscatter characteristics of scatterers within a sample. The primary difference between the method illustrated in FIG. 3a and the method illustrated in FIG. 4a that the method illustrated in FIG. 4a includes the steps of coherently demodulating the auto- and cross-correlation functions at the center wavenumber of the source prior to obtaining the auto- and cross-power spectrums, respectively. Additionally, each transfer function calculated is adjusted to shift the axis from the center wavenumber of the source, thereby ridding the effect of the demodulation steps.

As indicated in step 31a, the autocorrelation function over a predetermined depth D is acquired from an OCT system having an optical reflector in the sample arm; as indicated in step 41 the auto-correlation function is demodulated at the center wavenumber of the source; and as indicated in step 32a, the auto-power spectrum is obtained from the demodulated auto-correlation data by performing a Fourier transform on the demodulated auto-correlation data. As indicated in steps 33a, 42, 34a, 35a and 36a, multiple sets of cross-correlation data are obtained, where the distribution of scatterers within the sample has been altered for each acquisition or where the sample arm is repositioned slightly for each acquisition. As indicated in step 33a the cross-correlation function over a full length L is acquired from the OCT system having the biological tissue sample in the sample arm; next, as indicated in step 42, the cross-correlation function is demodulated at the center wavenumber of the source; next, as indicated in step 34a, the demodulated cross-correlation function is segmented into short segments of length D each to obtain depth resolved spectra with axial resolution D. As indicated in step 35a, it is determined whether a sufficient number of cross-correlation functions have been acquired; and as indicated in step 36, if more data is needed, the distribution of scatterers within the sample is altered or the sample arm is slightly repositioned prior to returning to step 33.

As indicated in step 37a, the cross-power spectrum is obtained from each of the demodulated cross-correlation functions by performing a Fourier transform on the cross-correlation function. As indicated in step 39a, a transfer function is determined for each cross-power spectrum by taking the ratio of each cross-power spectrum versus the auto-power spectrum. As indicated in step 43, each transfer function calculated is adjusted to shift the axis from the center wavenumber of the source, thereby removing the effect of the demodulation steps (see Equation 14(a)). And as indicated in step 40a, the magnitude of the backscatter spectrum C(k) is calculated by averaging the magnitudes of the squared transfer functions and then taking the square root of the average.

FIG. 4b illustrates a slightly modified version of the method illustrated in FIG. 4a. In particular, steps 33a and 34a of FIG. 4a are replaced with step 33a′ in FIG. 4b. As indicated in step 33′ the cross-correlation function over a full length L is acquired; however, the full length L is equal to the desired segment length D, and therefore, a step of segmenting the cross-correlation data is not required.

As shown in FIG. 5, an OCT data acquisition system 44 for performing the above method includes a low-coherence interferometer 46 and, preferably, a calibration interferometer 48. The low-coherence interferometer includes a radiation source 50, such as a super-luminescent diode (“SLD”) source, a fiber-optic source line 52 coupled between the SLD 50 and a fiber-optic beam splitter (such as a 50/50 fiber coupler) 54. The beam splitter separates the light received from the source line 52 into two beams; one transmitted to a sample arm 56 via an optical fiber 58, and the other to a reference arm 60 via an optical fiber 62. The fiber 58 is coupled to a sample probe 64 adapted to focus light to a sample 66 and to receive the light reflected back from the sample 66. The reflected light received back from the sample is transmitted back to the beam splitter 54 via the fiber 58. Preferably, the sample probe 64 has an adjustable focal length, thus allowing the adjustment of the focal spot size, working distance, and depth of focus.

The fiber 62 is coupled to a reference probe 68 adapted to focus the light received from the fiber 62 to a translating reference mirror 70 (usually mounted on a galvanometer), and to receive the light reflected back from the reference mirror 70. The reflected light received back from the reference mirror is transmitted back to the beam splitter 54 via the fiber 62. The reflected light received by the beam splitter 54, back from both the fiber 58 and fiber 62, is combined and transmitted on the fiber-optic line 72 to the photodetector 74. The photodetector 74 produces an analog signal 75 responsive to the intensity of the incident electric field. An example of a photodetector for use with the present invention is a Model 1811, commercially available from New Focus, Inc., Mountain View, Calif.

It will be apparent to one of ordinary skill in the art that there are many known methods and/or mechanisms for injecting the above reference arm delay, other than a translating reference mirror. All of these methods, of course, are within the scope of the present invention.

Alternative reference arm optical delay strategies include those which modulate the length of the reference arm optical fiber by using a piezo-electric fiber stretcher, methods based on varying the path length of the reference arm light by passing the light through rapidly rotating cubes or other rotating optical elements, and methods based on Fourier-domain pulse-shaping technology which modulate the group delay of the reference arm light by using an angularly scanning mirror to impose a frequency-dependent phase on the reference arm light after having been spectral dispersed. This latter technique, which is the first to have been shown capable of modulating the reference arm light fast enough to acquire OCT images at video rate, depends upon the fact that the inverse Fourier transform of a phase ramp in the frequency domain is equal to a group delay in the time domain. This latter delay line is also highly dispersive, in that it can impose different phase and group delays upon the reference arm light. For such a dispersive delay line, the OCT interferogram fringe spacing depends upon the reference arm phase delay, while the position of the interferogram envelope at any time depends upon the reference arm group delay. All types of delay lines can be described as imposing a Doppler shift frequency

f r = V ϕ k 0 2 π
on the reference arm light, where Doppler shift frequency in this context is defined as the time derivative of the phase of the central frequency component present in the interferometric signal {tilde over (R)}is(Δl). Vφ is the scan rate of optical phase delay in the reference arm. Vφ is also considered as scan rate of the optical phase delay difference between the reference and sample arms. This definition of Doppler shift frequency encompasses all possible reference arm delay technologies. The optical path length 76 of the sample arm 56 is different for reflecting and scattering sites at different depths (altering the scatterer distribution will change the reflector locations), while the optical path length 78 of the reference arm 60 changes with the translation of the reference mirror 70. Recording the detector current while translating the reference mirror 70 provides interferogram data, which is the optical path length dependent cross-correlation function {tilde over (R)}is(Δl) of the light retroreflected from the reference mirror 70 and the sample 66. Collecting interferogram data for a point on the surface of the sample for one reference mirror cycle is referred to as collecting an “A-scan.” The A-scan data provides a one-dimension profile of scattering information of the sample 66 verses depth.

The analog interferogram data signal 75 produced by the photodetector 74, for each A-scan, is sent through data processing scheme 80, designed to perform the steps as described above in FIGS. 3a-4b. The data processing scheme 80 includes an analog-to-digital converter 82 for converting the analog interferogram data 75 produced by the photodetector 74 into a digital interferogram signal 84. The digital interferogram signal 84 is sent to a windowed Fourier transform algorithm 86 for obtaining the cross-power spectrum {tilde over (S)}is(k) data 88. Windowed Fourier transform algorithm 86 uses a Fourier transform algorithm which is available in software libraries in commercially available software packages such as LabVIEW supplied by National Instruments, Austin, Tex.

The cross-power spectrum data is then sent to a processing algorithm 90 for calculating the transfer function estimate {tilde over (H)}′(k) data 92. The processing algorithm 90 is coupled to a memory 94 for storing the auto-power spectrum data and for storing the multiple transfer functions {tilde over (H)}′(k) used for calculating the backscatter spectrum C(k). To obtain the auto-power spectrum data, the sample 66 is replaced by a mirror 66′ and the data received by the photodetector 74 is the optical path length dependent auto-correlation function {tilde over (R)}ii(Δl) of the source light generated from the light retroreflected from the reference mirror 70 and the sample mirror 66′. The analog-to-digital converter 82 converts the analog auto-correlation function 75 into a digital signal and the Fourier transform algorithm 86 then obtains the auto-power spectrum {tilde over (S)}ii(k) data 88. When the processing algorithm 90 receives the auto-power spectrum {tilde over (S)}ii(k) data, it stores the data in the memory 94. Accordingly, the processing algorithm 90 will have access to the auto-power spectrum {tilde over (S)}ii(k) for calculating each estimate of the transfer function H(k) as described above.

Each estimate of the transfer function H(k) 92 is preferably obtained by the processing algorithm 90 according to the ratio of each cross-power spectrum {tilde over (S)}is(k) versus the stored auto-power spectrum {tilde over (S)}ii(k).

Once all of the transfer function estimates {tilde over (H)}′(k) 92 have been calculated, the transfer function estimates {tilde over (H)}′(k) are transmitted to an algorithm 96 for obtaining the average of the squared magnitudes of the transfer function estimates, and for calculating the backscatter spectrum estimate |{tilde over (C)}′(k)|2 98 by taking the square root of the average as discussed above with respect to step 40 of FIGS. 3a and 3b, and step 40a of FIGS. 4a and 4b. An algorithm 96 for use with the present invention may be implemented in commercially available software packages such as LabVIEW supplied by National Instruments, Austin, Tex.

Note that the operations described herein have been performed and tested in software using packages such as LabVIEW and MATLAB. It is also within the scope of the invention that these operations be performed by using hardware DSP devices and circuitry. For example, the Fourier transform algorithm 86, the processing algorithm 90 and the algorithm 96 may be performed by hardware devices or circuits specially designed to perform the steps as described above. Such hardware devices or circuits are conventional and thus will be apparent to those of ordinary skill in the art.

The backscatter spectrum C(k) 98 is transmitted to a computer 100 for comparison against backscatter data from a ‘normal’ tissue that is stored in the database 101. Additional applications for the backscatter spectrum C(k) 98 are given below. The computer 100 also preferably generates the control signals 104 for controlling the above process. For example, the computer may simultaneously control the lateral translation of the sample probe 64 and the translation of the reference mirror 70; and the computer 100 may also provide controls for coordinating the deconvolution scheme 80. Furthermore, it should be apparent to one of ordinary skill in the art, that the computer 100 could contain all or portions of the data processing scheme 80, or that the data processing scheme could be part of a separate analog or digital circuit, etc.

It will be apparent to those of ordinary skill in the art that a demodulation step/device may be incorporated to the system of FIG. 5 to demodulate the interferogram data 75 or 84 prior to the processing steps/components discussed above. For example, see FIG. 4b.

A preliminary demonstration of depth resolved spectroscopy using OCT is provided in FIG. 6. In the figure, the spectrum of the light incident on an interference filter is plotted along with the transfer function (i.e., spectral passband characteristic) corresponding to a double pass through the filter. The transfer function is obtained using Eq. 6 of the model developed above from an OCT A-scan of the filter, windowed to the vicinity of the glass-air interface from the rear side of the filter. Referring to FIG. 6, the spectrum of light (1) incident on a commercial interference filter (IF) and the transfer function characteristic (passband) resulting from a double pass through an interference filter (2) are plotted. Both spectra were obtained by separately gating and processing localized interferometric data resulting from Fresnel reflections at the front and rear surfaces of the filter, respectively. The measured spectral widths correspond well with the manufacturer's specifications (SLD: spectral width 47 nm FWHM; filter: bandwidth 10 nm FWHM single-pass).

IV. Depth Resolved Backscatter Fourier Transform Spectroscopy Application

In many diseases structural changes occur at the cellular and sub-cellular level in the affected organ. Examples of such changes include enlargement and changes in shapes of nuclei in colonic adenoma (which is a precursor to colonic cancer) and an increased population of inflammatory cells in ulcerative colitis. These scatterers in the tissue have dimensions comparable to the near infra-red wavelengths of the light source (e.g., 1250 nm to 1350 nm for the SLD in our laboratory). Therefore the scattering process is best described by the phenomenon of “Mie scattering” for which the backscattering cross-sections of these scattering sites are highly frequency dependent. In a typical histopathological assessment, changes in cellular structure are examined. These include changes in cellular as well as nuclear sizes and shapes and clustering patterns of the cells or nuclei. Variations in morphology affect the elastic scattering properties of cells. This variation in backscattering properties of the tissue microstructure could be exploited to diagnose various diseases. Depth resolved elastic backscattering spectroscopic information could aid in detecting the shapes and sizes of the lesions in an affected organ and thus assist in accurate staging of diseases such as the cancer.

Extracellular architecture as well as the sizes and shapes of cells and cellular components exhibit variations in different tissue types as well as in different layers within the same tissue. The frequency dependence of the elastic backscattering properties of biological materials is closely related to these morphological changes. Therefore this spectral information can be used in detecting shapes, sizes or refractive indices of various particles at different depths in the tissue specimen. This can be achieved since the backscattered spectrum is a function of shape, size and the refractive index of the particles and the refractive index of the surrounding medium.

This spectral information may also provide contrast mechanisms based on differential backscattering spectroscopic properties of the sites localized within different depth regions of the specimen. Range gated spectra thus obtained can be used to develop various contrast enhancement mechanisms. For instance, an OCT image obtained with complex envelope information can be displayed as a gray scale image using amplitude information. It is possible to compute spectra resolved at different depths in regular intervals using complex envelope data. This spectral information can be “color” coded (e.g., one can encode the peaks or widths of the spectra in various colors). Thus the gray scale image can be supplemented with this “color” information resulting in a colored OCT image. Better differentiation between the layers in OCT images could be achieved by using such a color information.

This spectral information could also be used to complement the diagnostic capability of OCT. Three dimensionally resolved spectroscopy could assist in studying the extent of infiltration of a disease such as cancer, database of spectral signatures of various layers of normal and abnormal tissue samples. The pathological states at different layers could be determined by comparing the spectra acquired at these layers with those in the database. Two dimensional lateral scanning of the tissue samples may provide the degree of invasion of diseases accurately.

V. Methods to Obtain Spectra at a Given Depth

As described in section III, the cross-correlation function {tilde over (R)}′is(Δl) corresponding to a lateral (or angular in endoscopy/catheterization applications) position of the sample probe over a full length L is acquired from the OCT system having the biological tissue sample in the sample arm and is segmented into short segments of length D each to obtain depth resolved spectra with axial resolution D. D is typically chosen to be longer than or equal to the source coherence length. These segments of cross-correlation data {tilde over (R)}′is(Δl) are called {tilde over (R)}is(Δl).

Here we elaborate on a method to obtain segments of {tilde over (R)}′is(Δl). First a starting depth and a window of depth range D is selected. At the selected starting depth, the values of digitized {tilde over (R)}′is(Δl) (i.e., {tilde over (R)}′is(n)) are selected corresponding to depth range D. The selected array corresponding to the depth range D is called digitized {tilde over (R)}is(Δl) (i.e., {tilde over (R)}is(n)) and is passed into a Fourier transform circuit or algorithm to obtain a power spectrum {tilde over (S)}is(k) for that particular depth range.

Next, at a predetermined point past the starting depth, another depth window of {tilde over (R)}is(n) is extracted from {tilde over (R)}′is(n). From this next depth window, {tilde over (S)}is(k) is calculated as described above. New windows will thereafter be repeatedly extracted and processed to generate a complete spectral profile for the particular {tilde over (R)}′is(Δl).

This operation can be summarized by the following equation (known as windowed Fourier transform (WFT) equation):

S ~ is ( n Δz , qk p ) = [ m = - N / 2 N / 2 - 1 R ~ is [ ( n + m ) Δz ] exp [ - jqk p m Δz ] w ( m Δz ) ]
where w(mDz) is the analysis window through which the sampled space-domain cross-correlation function {tilde over (R)}′is(n) is shifted, Dz is the sampling interval, and N is the number of samples contributing to the local spectral estimate centered at depth nDz.

Thus N samples of {tilde over (S)}is(nΔz, k) are acquired. {tilde over (S)}is(nΔz, qkP) is {tilde over (S)}is(k) measured at depth nDz. Here kP=1/(NΔz) is the sampling interval in wavenumber domain, and q is an integer. The numbers

S ~ is ( n Δz , - ( N 2 ) k p ) , S ~ is ( n Δz , - ( N - 2 2 ) k p ) , S ~ is ( n Δz , qk p ) S ~ is ( n Δz , - ( N - 1 2 ) k p )
denote N measurements of a the cross-power spectrum sampled at spatial frequencies

Nk p / 2 , - ( N - 2 2 ) k p , qk p ,
Thus the spatial resolution of the spectral estimate is given by the window size (NDz), the larger the window—the lower the spatial resolution. But spectral estimation precision kP is inversely related to the window size and is given by
kP=1/(NΔz)
This equation is derived using discrete Fourier transform properties. Thus the larger the window—the better the spectral resolution.

If {tilde over (R)}′is(Δl) is coherently demodulated to obtain the complex envelope {tilde over (R)}′is(Δl), then a similar procedure provides depth resolved spectra. As described in section III, the cross-correlation function {tilde over (R)}′is(Δl) corresponding to a lateral (or angular in endoscopy/catheterization applications) position of the sample probe over a full length L is acquired from the OCT system having the biological tissue sample in the sample arm and is segmented into short segments of length D each to obtain depth resolved spectra with axial resolution D. D should be longer than or equal to the source coherence length. These segments of cross-correlation data {tilde over (R)}′is(Δl) are called {tilde over (R)}′is(Δl).

Here we elaborate on a method to obtain segments of {tilde over (R)}′is(Δl). First a starting depth and a window of depth range D is selected. At the selected starting depth, the values of digitized {tilde over (R)}′is(Δl) (or {tilde over (R)}′is(n)) are selected corresponding to depth range D. The selected array corresponding to the depth range D is called digitized {tilde over (R)}is(Δl) (or {tilde over (R)}is(n)) and is passed into a Fourier transform circuit or algorithm to obtain a power spectrum Sis(k) for that particular depth range.

Next, at a predetermined point past the starting depth, another depth window of Ris(n) is extracted from {tilde over (R)}′is(n). From this next depth window, Sis(k) is calculated as described above. New windows will thereafter be repeatedly extracted and processed to generate a complete spectral profile for the particular {tilde over (R)}′is(Δl).

This operation can be summarized by the following equation:

S is ( n Δz , qk p ) = [ m = - N / 2 N / 2 - 1 R is [ ( n + m ) Δz ] exp [ - jqk p m Δz ] w ( m Δz ) ]
Sis(nΔz, qkP) is Sis(k) measured at depth nDz.

Thus the spatial resolution of the spectral estimate is given by the window size (NDz), the larger the window—the lower the spatial resolution. But spectral estimation precision kP is inversely related to the window size and is given by
kP=1/(NΔz)
This equation is derived using discrete Fourier transform properties. Thus the larger the window—the better the spectral resolution.

Several types of analysis windows may be used in the circuit/algorithm, including rectangular, Bartlett (triangular), Hamming, Hanning, Blackman windows. It is well known to those skilled in the art that the choice of window may affect the power spectrum estimation accuracy. In our experiments we used a simple rectangular window. An alternative implementation of the window is to pad the N-point analysis window with zeros on either side, increasing its length in order to enhance the frequency precision. The size (length) of the window is indicated as NDz which must be shorter than the entire A-scan length L. While a user may choose the window length as short as he wishes, it may be apparent to those of ordinary skill in the art that due to the interference from the reflectors located within a coherence length, the axial resolution is limited by the coherence length. Therefore it is desirable to choose the window length longer than or equal to the coherence length.

The above steps for converting the interferogram data into power spectrum data may be performed by a bank of narrow-band band-pass filters (NBPF), where each NBPF passes a particular wavenumber along the power spectrum wavenumber scale. The outputs of each NBPF may be input directly into the transfer function calculation. This method eliminates the need for the windowed Fourier transform circuit/algorithm and, may also eliminate the need for the coherent demodulation circuit/algorithm. Thus, this method provides faster and cheaper signal processing.

These NBPF may also be implemented by a bank of demodulators and a corresponding bank of low-pass filters, where each demodulator demodulates the data at a particular wavenumber along the power spectrum frequency scale and each corresponding low-pass filter filters the output of the demodulator to only pass a narrow band of wavenumbers as desired by users.

These NBPF can be applied directly to {tilde over (R)}′is(Δl) or {tilde over (R)}′is(Δl) to obtain {tilde over (S)}′is(k) or Sis(k), respectively. Also, one may demodulate {tilde over (R)}′is(Δl) at a wavenumber other than k0 to produce a signal which can be fed to NBPF to eventually generate {tilde over (S)}is(k) or Sis(k).

Thus in this alternate embodiment of the present invention, the necessity of a windowed Fourier transform step to produce the power spectra may {tilde over (S)}is(k) or Sis(k) may be eliminated by utilizing a bank of narrow-band band-pass filters (“NPBFs”), where each NBPF passes a particular frequency along the power spectrum frequency scale.

As shown in FIG. 7, a bank of NBPFs 130 may be positioned to filter the raw, (non-demodulated) photodetector signal 75 and produce the cross-power spectrum 88′. From the cross-power spectrum 88′ the processing algorithm 90 is used to generate a transfer function and the algorithm/circuit 96 is used to calculate the backscatter spectrum estimate. The bank 130 comprises N NBPFs, each having a bandwidth of approximately (Vg/NDz). Here Vg is the scan rate of the group delay of the reference arm as compared to the sample arm. Vg=2Vr for a simple mechanically translated reference mirror. Such a filter provides spatial frequency precision given by kP=1/(NΔz). The center frequency of each NBPF corresponds to a particular wavenumber along the wavenumber scale of a power spectrum {tilde over (S)}is(k), centered at the source center wavenumber k0. If fc is the center frequency of a band-pass filter (BPF), then, the corresponding wavenumber is given by:

k = k o ( 1 - V ϕ V g ) + f c V g 2 π
For a simple mechanically translated reference mirror, Vg=Vf=2Vr

k = f c V r π
Thus, some of the NBPFs will pass frequencies below the Doppler shift frequency of the reference arm fr, and the rest will pass frequencies above the reference arm Doppler shift frequency fr. For example, the middle NBPF will be centered at the reference arm Doppler shift frequency,fr; the next NBPF above the center NBPF will be centered at the frequency fr+Vg/NDZ; and the next NBPF below the center NBPF will be centered at the frequency fr−Vg/NDZ. In this alternate embodiment, the coherent demodulation circuit/device and the windowed Fourier transform circuit/step are not needed.

Alternatively, as shown in FIG. 8, the photodetector signal 75 is demodulated at the center wave number of the source, by demodulation step/device 132, to produce analog in-phase “I” 134 and analog quadrature “Q” data 136. A bank of complex NBPFs 138 are positioned after the coherent demodulation step/device 132, where each receives both the analog in-phase “I” 134 and the analog quadrature “Q” 136 components of Ris(Δl). The bank 138 comprises NBPFs, each having a bandwidth of approximately Vg/NDz, where the center frequency of each NBPF corresponds to a particular wavenumber along the wavenumber scale of the power spectrum Sis(k) 88″ centered at zero wavenumber. Thus, some of the NBPFs will pass frequencies below zero, and the rest will pass frequencies above zero. The middle NBPF will be centered at zero frequency; the next NBPF above the center NBPF will be centered at the frequency Vg/NDz; and the next NBPF below the center NBPF will be centered at the frequency—Vg/NDz. In this alternate embodiment, the windowed Fourier transform circuit/step is not needed. From the cross-power spectrum 88″ the processing algorithm 90 is used to generate a transfer function and the algorithm/circuit 96 is used to calculate the backscatter spectrum estimate. As discussed above in FIGS. 4a and 4b, because a deconvolution step was performed on the interferogram data, the axis of the transfer function must be shifted to remove the effect of demodulation.

If fc is the center frequency of a band-pass filter (BPF), then, the corresponding wavenumber is given by:

k = k o + f c V g 2 π
It will be apparent to one of ordinary skill in the art that the array of complex NBPFs may be replaced by two arrays of NBPFs, one array for the in-phase data, and one array for the quadrature data; and the square-root of the sum of the squares of the output of each array will yield the resultant power spectrum Sis(k).

Finally, as shown in FIG. 9, the interferometer signal 75 can be coherently demodulated at frequency fI, as shown in block 140, to produce in-phase data 142 and quadrature data 144. The in-phase and quadrature data is fed into a bank of complex NBPFs 146 to generate a cross-power spectrum 88′″. The bank comprises N NBPFs, each having a bandwidth of approximately Vg/NDz, where the center frequency of each NBPF corresponds to a particular wavenumber along the wavenumber scale of a power spectrum centered at frequency fI. Thus, some of the NBPFs will pass frequencies below fI, and the rest will pass frequencies above fI. The middle NBPF will be centered at fI, the next NBPF above the center NBPF will be centered at the frequency fr−fI+Vg/NDz; and the next NBPF below the center NBPF will be centered at the frequency fr−fI−Vg/NDz. The wavenumber k is given by:

k = k o ( 1 - V ϕ V g ) + f c + f I V g 2 π
In this alternate embodiment, the windowed Fourier transform circuit/step is not needed. From the cross-power spectrum 88″ the processing algorithm 90 is used to generate a transfer function and the algorithm/circuit 96 is used to calculate the backscatter spectrum estimate. As discussed above in FIGS. 4a and 4b, because a deconvolution step was performed on the interferogram data, the axis of the transfer function must be shifted to remove the effect of demodulation.

It will be apparent to one of ordinary skill in the art that the array of complex NBPFs may be replaced by two arrays of NBPFs, one array for the in-phase data, and one array for the quadrature data; The frequency fI is selected such that the NBPFs are centered in the few kHz frequencies. Such NBPFs are cheaper, and more readily available than NBPFs centered in the frequencies near the reference arm Doppler shift frequency fr.

The banks of NBPF, discussed above, may also be replaced by a bank of demodulators and low-pass filters, where the demodulation frequency is same as the center frequency of the corresponding BPF and each corresponding low-pass filter has a bandwidth as desired by users.

It should be obvious to one skilled in the art that the approach of using a bank of NBPF's or demodulators to obtain spatially-localized frequency information is quite general, and is not necessarily limited to the case of using all NBPF's symmetrically distributed around the reference arm Doppler shift frequency, or around baseband or at evenly spaced frequencies, or even all with the same pass bandwidth. The user may have the option to select any frequency to monitor, with any bandwidth desired.

VI. Method to Measure Actual Spectrum of the Light in the Sample Arm

Following from the model described above in Section II, the present invention also provides a system/method for determining or measuring the actual spectrum {tilde over (S)}ss(k) of the light in the sample arm 56. As shown in FIG. 10a, a first embodiment of this method includes a step 148 of obtaining an auto-power spectrum according to any of the procedures described herein; a step 150 of obtaining multiple cross-power spectrum readings from the interferometer signal according to any of the procedures described herein, where the distribution of the scatterers within the sample is altered with respect to the sample arm for each reading; and a step 152 of calculating the spectrum {tilde over (S)}ss(k) of the light in the sample arm according to the following equation:
{tilde over (S)}ss(k)=E{|{tilde over (S)}is(k)|2}/{tilde over (S)}ii(k)

As shown in FIG. 10b, an alternate embodiment of this method includes a step 154 of obtaining a demodulated auto-power spectrum according to any of the procedures described herein; a step 156 of obtaining multiple demodulated cross-power spectrum readings from the interferometer signal according to any of the procedures described herein, where the distribution of the scatterers within the sample is altered with respect to the sample arm for each reading; a step 158 of adjusting the axis of each of the demodulated auto- and cross-power spectra to remove the effect of the demodulation step; and a step 160 of calculating the spectrum {tilde over (S)}ss(k) of the light in the sample arm according to the following equation:
{tilde over (S)}ss(k)=E{|{tilde over (S)}is (k)|2}/{tilde over (S)}ii (k)
VII. Reference Arm Optical Path-length Calibration

It is advantageous, in the above data processing scheme, that the auto-correlation and cross-correlation functions be measured with the sub-micron accuracy. Therefore, to enhance the accuracy of the low coherence interferogram acquisition, a long coherence length calibration interferometer 48 is incorporated into the system to accurately monitor and compensate for the inevitable velocity fluctuations of the reference mirror 70.

As shown in FIG. 5, the calibration interferometer 48 includes a long-coherence length, narrow-band laser illumination source 106, such as a helium neon (He—Ne) laser or a distributed feed-back diode laser (DFB diode laser), a reference probe 108, and a sample probe 110. The narrow-band illumination source must have a coherence length that is longer than the region (depth) in the sample 66 that is being scanned (for example, the He—Ne laser has a coherence length of several meters).

The illumination source 106 transmits to a beam splitter 111, which separates the source signal into two illumination source signals, one being transmitted to the reference probe 108 and the other being transmitted to the sample probe 110. The reference probe 108 focuses its illumination source signal to the mirror 70′ mounted on the back of the reference mirror 70 which is mounted on the galvanometer, and the sample probe 110 transmits its illumination source signal to a fixed mirror 112. The interferometer also includes a photodetector 114 for receiving the combination of light reflected back from the reference mirror 70 and the fixed mirror 112, and for producing an analog signal 115 corresponding to the intensity of light received. Because a long-coherence length illumination source 106 is used, the analog interferometric signal 115 produced by the photodetector 114 will be a relatively constant amplitude sinusoidal signal, having a frequency equal to the Doppler shift corresponding to velocity fluctuations in the reference mirror 70 experienced by the electric field in the reference arm.

The analog signal 115 produced by the photodetector 114 is sent to an interval-detect circuit 116, for detecting features in the signal 115 that are regular in time (such as zero crossings). These features 118 are fed into a clock generator circuit 120 for generating a digital clock source signal 122 for clocking (triggering) the analog-to-digital converter device 82 used in the deconvolution scheme 80. Accordingly, the sampling rate of the analog-to-digital converter 82 will be synchronized according to the fluctuations in the reference mirror 70 translation velocity detected by the calibration interferometer 48. Examples of interval-detect and clock generator circuits for use with the present invention include Tektronix 465 oscilloscope, commercially available from Tektronix, inc.

As will be apparent to those of ordinary skill in the art, there are many way to use the calibration interferometer 48 to compensate for the inevitable velocity fluctuations in the reference mirror speed; all of which are within the scope of the present invention. For example, an alternate method for incorporating the narrow-band illumination source calibration interferometer into the data acquisition system includes the steps of: digitizing both the calibration and the SLD interferograms at a sampling rate that is higher than twice the frequency of the calibration interferogram; detecting regular features, corresponding to regular intervals of space, of the calibration interferogram (e.g., zero crossings) using a thresholding or pattern recognition algorithm; and re-sample the SLD interferogram data at the regular intervals using interpolation routines.

VIII. Stimulated Coherent Spectroscopic Optical Coherence Tomogaphy (SC-SPOCT)

The present invention also provides a system and method for performing three-dimensionally resolved coherent spectroscopy by taking advantage of the depth-resolving capability of OCT. In principle, any coherent scattering process may be detected by OCT, as long as the scattered light remains within the bandwidth of the OCT source light spectrum. In particular, we disclose a method for depth-resolving stimulated coherent scattering processes using a system based upon the SPOCT concept. Stimulated coherent scattering processes involve a transfer of energy from photons in an intense pump beam and from excited states of an atom or molecule to a typically weaker probe beam. The probe photon frequency is typically Stokes shifted (i.e., is at a lower frequency) from the pump photon frequency. Examples of stimulated coherent scattering processes include stimulated emission, stimulated Raman scattering, coherent anti-Stokes Raman scattering (in which case the probe photon frequency is higher than the pump photon frequency) stimulated Brillouin scattering, stimulated Rayleigh scattering, stimulated Rayleigh-wing scattering, four-wave mixing, and others which are well known to those practiced in the art. In typical stimulated scattering experiments, the pump photons are provided by an intense laser pump source, and the probe photons are either provided by a weak probe beam or are provided by incoherent scattering processes or noise. The operation of a laser, for example, is based on stimulated emission of radiation at the laser oscillation frequency which builds up from optical noise present in the laser cavity due to a spontanous (i.e., incoherent) emission background. In stimulated Raman scattering experiments, the probe beam may either be supplied as a weak source at a frequency corresponding to the Raman transition to be interrogated in the sample, or it may also be allowed to build up from incoherent spontaneous Raman scattering noise. In either case, the intense pump radiation sets up a condition in which the probe experiences frequency-dependent coherent gain in the medium. The frequency dependence of the gain is determined by the medium's specific atomic and molecular composition; thus probing the frequency dependence of the stimulated gain may serve as a sensitive probe of tissue biochemistry with applications in medical diagnostics. In typical experiments of this type, the probe radiation is monochromatic and the gain experienced in traversing an excited medium is measured using either direct, gated, or synchronous detection techniques as the frequency of the probe radiation is scanned. The primary idea of stimulated coherent spectroscopic OCT is to take advantage of the broad spectral content of OCT probe light in combination with a separate pump light beam to perform stimulated coherent spectroscopy over the whole source spectrum at once, while simultaneously using the short coherence length of the OCT probe light to depth resolve the resulting stimulated scattering spectrum.

Referring again to FIG. 5, in stimulated coherent spectroscopic OCT an intense pump laser 130 is directed to the sample 66 at the appropriate frequency to induce depth- and frequency-dependent gain in the sample volume interrogated. The depth resolved sample scattering spectrum {tilde over (C)}(k)2 or sample arm power spectrum {tilde over (S)}ss(k) obtained according to the steps discussed above will thus contain features corresponding to the frequency-dependent round-trip gain experienced by the OCT source radiation (inelastic backscattering characteristics of the scatterers resident within the window). Specific means for combining the pump and probe beams in SC-SPOCT are illustrated in FIGS. 11a and 11b.

For stimulated scattering processes which do not require phase matching between the pump and probe beams, the pump beam may be directed into the sample at any angle with respect to the probe beam. A convenient design is thus to combine the pump and probe beams coaxially, as illustrated in FIGS. 11a and 11b. In the bulk optic SC-SPOCT system illustrated in FIG. 11a, the pump light 130 is combined with the sample arm light 204 in beamsplitter #2 206 which may be either a broadband, wavelength-independent beamsplitter (similar to beamsplitter #1), or else preferably may be a dichroic beamsplitter which preferentially reflects the pump laser light and passes the OCT probe light. It should be obvious that beamsplitter #2 206 may be placed at any point in the sample arm of the interferometer either before or after the sample arm focusing optics. Also, beamsplitter #2 may also be placed before beamsplitter #1 54, although this is not a preferred embodiment since interference between the long-coherence-length pump light in the sample and reference arms will make detection of the probe light interference more difficult. Several other modifications to the normal OCT setup are required for SC-SPOCT. Since some of the intense pump light may be reflected from the sample and hence re-coupled into the interferometer, some optical elements designed to protect sensitive interferometer components and allow for optimal performance may be added. These may include an optical isolator 212 placed immediately after the OCT broadband source, and a wavelength-selective filter 216 placed before the detector 74. The wavelength-selective filter 216 may be a wavelength long-pass filter in the typical case in which the pump laser frequency is higher than the probe light frequency, or else it may be a wavelength short-pass filter in the opposite case or a interference band-pass (at the OCT probe wavelength) or band-reject (at the pump laser wavelength) filter in either case. It should also be noted that the sample arm optics depicted in FIGS. 11a and 11b are only a schematic representation of whatever sophisticated optics may be present in the actual interferometer, including, for example, the relay coupling and focusing optics of a biomicroscope, endoscope, catheter, or other medical diagnostic device. Finally, a timing trigger 220 may be provided for the purpose of gated or synchronous detection (described later). This trigger may be derived from an independent trigger source, or from the trigger electronics of either the pump laser or OCT probe source. The trigger may also be obtained from detection of a small pick-off beam from either the pump laser or OCT probe light source, in a manner which is familiar to those skilled in the art.

FIG. 11b depicts the coaxial combination of the pump and probe light in the case of a fiber optic OCT system, in which all of the extra elements are present in their fiber optic implementation but have the same role as their counterparts in the bulk optic system of FIG. 11a. In this case, the fiber optic version of the dichroic implementation of beamsplitter #2 is know as a wavelength division multiplexer (WDM). FIG. 11c illustrates the case in which the pump laser light and the OCT probe light are not delivered to the sample coaxially, but rather are delivered through either the same or separate optical focusing systems in such a way that they arrive with an angle θ between them. This arrangement may be used when the coaxial system of FIGS. 11a and 11b is not practical, or else when a specific angle between the pump and probe beams is required to meet a phase matching condition.

The concept and process of SC-SPOCT is illustrated schematically in FIG. 12a-12e. OCT probe light 50 with a source spectrum given by {tilde over (S)}ii(k) is incident in the source arm of the SC-SPOCT interferometer. This light may have an arbitrary spectral shape, but it is characterized by a center spatial frequency k0 and a full-width-half-maximum (FWHM) spectral bandwidth Δk0. Light from the pump source 130 which is incident on the second beam splitter is also characterized by its center frequency k1 and FWHM spectral bandwidth Δk1. In the preferred embodiment of SC-SPOCT, Δk1 will be much narrower than Δk0, and in fact Δk1 will set the maximum spectral resolution with which the stimulated coherent scattering features of the sample will be resolved. The spectrum of light incident on the sample will thus be a superposition of the source and pump spectra, as illustrated in the figure. The sample is characterized by its own intrinsic stimulated scattering spectrum {tilde over (C)}(k)2 which is a function of the pump wavelength k1 and the internal atomic/molecular makeup of the sample. In the example of FIG. 12d, the stimulated scattering spectrum is characterized by several separate coherent scattering peaks corresponding to internal electronic or vibrational/rotational transitions of the atoms and molecules within the sample, each peak having its own center frequency and spectral bandwidth. In the case of stimulated emission SPOCT, the stimulated scattering spectrum will reflect electronic energy states comprising the fluorescence spectrum of the sample having been stimulated with light at the spatial frequency k0. In this case, the stimulated scattering peaks will be quite broad (typically several hundred nanometers bandwidth in the wavelength units typically used in atomic spectroscopy), in many cases as broad or broader than the spectral bandwidth of the OCT probe source itself. In the case of stimulated Raman scattering, the stimulated scattering spectrum will reflect the Raman spectrum of the sample as a function of the frequency offset from the excitation frequency k1, and the bandwidth of the peaks will typically be on the order of single cm−1 to tens of cm−1, in the spatial frequency units typically used in molecular spectroscopy.

As illustrated in FIGS. 12a-12e, the pump laser beam at frequency k1 will induce a gain with frequency dependence given by {tilde over (C)}(k)2 in the sample, and thus the light collected by the sample arm optics the sample will contain a combination of elastically and inelastically scattered light whose composite spectrum will appear as illustrated. This composite spectrum will have the overall shape of the source spectrum, however for those frequencies in the stimulated spectrum of the sample {tilde over (C)}(k)2 which overlap the source spectrum, stimulated gain will lead to alterations in the collected spectrum reflecting the frequency-dependent gain of the sample. The stimulated spectrum of the sample {tilde over (C)}(k)2 and the power spectrum of the light returning from the sample {tilde over (S)}ss(k) may both be recovered as a function of depth in the sample using the methods described in the previous sections of this disclosure.

In general, the spectrum of light returning from the sample {tilde over (S)}ss(k) and the sample backscatter spectrum estimate {tilde over (C)}(k)2 will include alterations due to the elastic basckscatter spectrum of the sample as well as due to stimulated scattering processes. Methods for isolating the stimulated scattering spectrum with high sensitivity by using gated or synchronous detection are described in the next paragraph. Assuming that the alterations to the backscatter spectrum are either small compared to alterations due to stimulated coherent scattering, or else have been otherwise removed, a method for extracting a quantitave parameter for the stimulated scattering spectrum from estimates of {tilde over (S)}ss(k) is next described. Here we extend the notation for {tilde over (S)}ss(k) to {tilde over (S)}ss(l,k) to denote the sample arm power spectrum estimated at a distance into the sample of l. We denote the frequency-dependent gain of the sample at a depth l as {tilde over (G)}(l,k), and note that for stimulated coherent scattering processes the sample arm light will experience exponential gain between any two depths l1 and l2 in the sample as a function of {tilde over (G)}(l,k) and the round-trip propagation distance l2−l1:
{tilde over (S)}ss(l2,k)={tilde over (S)}ss(l1,k)·exp[2{tilde over (G)}(l1:l2,k)·(l2−l1)]·  (AA)
Here {tilde over (G)}(l1:l2,k) denotes the stimulated scattering gain specified over the depth range from l1 to l2.

FIG. 13 illustrates how the SC-SPOCT sample arm power spectrum will be modified as a function of propagation depth in a sample with stimulated scattering. Estimates of {tilde over (G)}(l1:l2, k) may be obtained from estimates of {tilde over (S)}ss(l,k) by solving equation AA:

G ~ ( l 1 : l 2 , k ) = 1 ( l 2 - l 1 ) Ln [ S ~ ss ( l 2 , k ) S ~ ss ( l 1 , k ) ] . ( BB )

The actual stimulated coherent gain experienced in tissues in most cases will be very small, perhaps altering the sample arm power spectrum by as little as 1 part in 103 or even 1 part in 106. In addition, as mentioned above, the stimulated scattering spectral alterations will occur in addition to spectral alterations due to elastic backscatter. It would thus be very desirable to have a method to isolate very small stimulated coherent alterations.

Methods for using gated or synchronous detection to achieve this objective are illustrated in FIGS. 14a-b and 15a-b. The underlying idea of these methods is to employ modulation of the pump light source power to modulate only those component of the estimated sample arm power spectrum which are due to stimulated scattering effects.

Gated detection of stimulated coherent scattering is illustrated schematically in FIG. 14a. For gated detection, a pulsed pump laser is used. The pump laser light may be pulsed either by using a Q-switched or mode-locked laser. Gated detection is the optimal detection method for stimulated coherent scattering processes for which the stimulated gain coefficient {tilde over (G)}(l,k) is a function of the pump laser intensity, i.e. for nonlinear optical processes such as stimulated Raman scattering. For higher-order nonlinear optical stimulated scattering processes, it may also be advantageous to use a pulsed OCT probe source synchronized to the pump laser pulse frequency, such as the broadband output of a femtosecond mode-locked laser. In gated detection, the pump laser is triggered by a timing trigger source which may be either a separate system trigger, or may be a part of the pump laser pulse electronics. The detector 74 output is then processed by a gated integrator device 224, which integrates the detector output only for the duration of a gate which is set to coincide with the laser pulse duration. The gated integrator outputs a signal 226 representing the average of the signal detected during the gate, optionally additionally averaged over many separate laser pulses. The gated integrator also outputs a signal 228 proportional to the average of the signal detected during a separate gate signal when the pump laser is not on, also optionally averaged over many separate such gates. These two outputs are then digitized in A/D converters 230, 232, one or more times per coherence length of travel of the reference arm of the SC-SPOCT interferometer. In the computer 234, these digitized values are processed (using the methods described above) to generate estimates of {tilde over (C)}(k)2 and/or {tilde over (S)}ss(l,k) both with and without the pump laser on. The estimate of {tilde over (C)}(l,k) and/or {tilde over (S)}ss(l,k) obtained with the laser on is subtracted from the estimate obtained with the laser off, generating a high sensitivity measurement of {tilde over (C)}(k)2 and/or {tilde over (S)}ss(l,k) due only to coherent scattering processes which is insensitive to the elastic backscatter spectrum.

Synchronous detection of stimulated coherent scattered light is illustrated in FIG. 15a-b. In synchronous detection, the intensity of the pump laser light is modulated at a frequency f0. Modulation of the pump laser light may be accomplished either sinusoidally by modulating the pump laser power supply, or optically by use of electro-optic or acousto-optic modulation. Alternatively, the pump laser light may be modulated with a square wave amplitude profile by use of an optical chopper. In synchronous detection, the detector 74 signal and a trigger 220 signal with a fixed phase relationship to the pump laser modulation are provided as signal and reference inputs, respectively, to a lock-in amplifier 236. The lock-in amplifier 236 outputs a signal proportional to the content of the detector signal which is modulated at the same frequency as and is in phase with the pump laser modulation. The lock-in amplifier output is digitized one or more times per coherence length of travel of the reference arm, and estimates of {tilde over (C)}(k)2 and/or {tilde over (S)}ss(l,k) both with and without the pump laser on are obtained as for gated detection.

IX. Stimulated-Emission Spectroscopic Optical Coherence Tomography (SE-SPOCT)

Stimulated emission spectroscopic optical coherence tomography (SE-SPOCT) is a specific implementation of stimulated coherent spectroscopic OCT which obtains a depth-resolved stimulated emission spectrum of a sample. SE-SPOCT may be used to image uptake of high quantum efficiency laser dyes or infrared-emitting exogenous fluorescent probes into biological specimens. Examples of the latter include probes for measurement of intra-cellular pH (e.g. carbocyanine, with an excitation maximum at 780 nm and an emission maximum at 795 nm), and nucleic acids (e.g. IR-132, with its excitation maximum at 805 nm and its emission maximum at 835 nm). A suitable pump laser 130 for use with such dyes includes a 780 nm nanosecond-pulsed fiber-coupled diode laser. When such a pump laser is utilized, an 830 nm superluminescent diode is used as the OCT probe source 50. Another pump laser 130 suitable for use with these or other infrared-emitting fluorescent species is a Nd:YAG-pumped dye laser. When such a pump laser is utilized, a modelocked Ti:Al2 0 3 laser may be used as a very broadband OCT probe source 50. The latter combination of pump and probe sources forms a broadly tunable system capable of detecting both depth- and frequency-dependent gain in a range of clinically viable probes.

X. Raman Scattering Spectroscopic OCT(SRS-SPOCT)

Similar to SE-SPOCT, the present invention also provides a system or method for performing stimulated Raman scattering spectroscopic OCT (SRS-SPOCT). In this embodiment, the system or method includes the means for, or the step of directing a high intensity pump light into the sample interaction region. Resonant gain experienced by the low-coherence probe light will appear as localized peaks in the depth-resolved backscatter spectrum of the sample. The SC-SPOCT concept is well suited to Raman spectroscopy since SRS spectra have sharp spectral features, and can be obtained in any desired wavelength range by selection of the pump laser frequency. Thus substantial vibrational/rotational spectral information can be collected using relatively narrow bandwidth OCT probe sources. In addition, coherent detection of Raman signals avoids incoherent fluorescent noise typical of other systems. Although SRS signals have not previously been observed in turbid media, coherent Raman gain spectroscopy has been demonstrated with low-power (including cw) laser sources using nonlinear interferometry.

SRS-SPOCT may be implemented using a modelocked, Q-switched Nd:YAG laser operating at 1060 nm as a pump source and a femtosecond Cr:Forsterite laser with a bandwidth extending from 1250 nm-1350 nm as the SPOCT probe. Assuming SRS gain cross sections typical of organic solvents, modelocked peak pump powers of ˜1 MW focused to the OCT probe beam spot size will be sufficient to generate ˜1% stimulated Raman gain over a 100 μm window depth in samples. The wavenumber shift available for depth-resolved spectral acquisition with this SRS-SPOCT implementation will encompass 1100-2000 cm−1, including most of the “fingerprint region” used in previous Raman spectroscopy studies of biological media. Many biological molecules have Raman shifts in this range, including proteins with Amide I (1645-1680 cm−1) and Amide III (1225-1300 cm−1) bands which can be used to characterize the α-helix, β pleated sheet and disordered protein conformations, and DNA base vibrations (1100-1700 cm−1) which can be used to differentiate B and Z conformations. SRS-SPOCT can be used to probe the structure of nuclear proteins and DNA, as well as the cytoplasmic and extracellular protein structure in human tissues.

XI. Conclusion

While describing the present invention, we talk about the scanning Michelson interferometer where the reference arm length is mechanically scanned by translating the reference mirror. It is to be understood that the inventions described herein are applicable to any interferometric device which estimates the correlation functions described above. The deconvolution algorithms are also applicable to any device which measures the auto-power spectra and cross-power spectra. Thus, the present invention is applicable to any device capable of measuring any of the above mentioned quantities whether the device operates in free space or is fiber optically integrated. Also, the present invention is equally applicable in situations where a measuring device is coupled to an endoscope or a catheter or any other diagnostic instrument.

The transfer function was described above as a function of spatial frequency (i.e., wavenumber k=2p/l,l is wavelength in the medium). It is to be understood that the transfer function can also be estimated using our methods as a function of optical frequency f′. Note that f′ can be related to k by f′=ck/(2p) where c is phase velocity in the medium at that wavenumber. Also, it is obvious that the transfer functions can also be expressed as a function of w=2pf′ or k1=1/l.

Although a low temporal coherence source is useful in making the measurements in OCDR and OCT, it is to be understood that a high temporal coherence source can also be used with the spectroscopy methods of the present invention.

Having described the invention in detail and by reference to the drawings, it will be apparent that modification and variations are possible without departing from the scope of the invention as defined in the following claims.

Claims (60)

1. A method for determining depth-resolved backscatter characteristics of scatterers within a sample, comprising the steps of:
acquiring a plurality of sets of cross-correlation interferogramn data using an interferometer having a sample arm with the sample in the sample arm, wherein the sample includes a distribution of scatterers therein, and wherein the acquiring step includes the step of altering the distribution of scatterers within the sample with respect to the sample arm for substantially each acquisition; and
averaging, in the Fourier domain, the cross-correlation interferogram data, thereby revealing backscattering characteristics of the scatterers within the sample.
2. The method of claim 1, wherein the averaging, in the Fourier domain, step includes the steps of:
calculating a transfer function for each set of cross-correlation interferogram data acquired; and
squaring the magnitude of each transfer function; and
averaging the squared magnitudes.
3. The method of claim 2, wherein the transfer function calculating step includes the steps of:
acquiring auto-correlation interferogram data for the interferometer;
generating, from the auto-correlation interferogram data, an auto-power spectrum;
generating, from the set of cross-correlation interferogram data, a cross-power spectrum; and
obtaining a ratio of the cross-power spectrum to the auto-power spectrum.
4. The method of claim 1, wherein the step of altering the distribution of scatterers within the sample with respect to the sample arm includes the step of physically altering the distribution of scatterers within the sample.
5. The method of claim 1, wherein the step of altering the distribution of scatterers within the sample with respect to the sample arm includes the step of repositioning the sample arm.
6. The method of claim 1, further comprising the step of comparing the backscattering characteristics with control data to diagnose abnormalities or disease within the sample.
7. The method of claim 6, further comprising the steps of incorporating a sample probe of the interferometer into an endoscope or surgical instrument and scanning the endoscope or surgical instrument along a portion of a patient's gastrointestinal tract tissue to diagnose abnormalities or disease within the patient's gastrointestinal tract tissue, wherein the control data includes data corresponding to backscattering characteristics of relatively normal gastrointestinal tract tissue.
8. The method of claim 1, wherein the acquiring cross-correlation interferogram data step or the averaging step includes the step of controlling the depth over which cross-correlation interferogram data is averaged.
9. The method of claim 8, wherein the interferometer includes a reference arm and the controlling step includes the step of limiting a scan length of the reference arm to an area of interest in the sample.
10. The method of claim 8, wherein the controlling step includes the step of windowing the cross-correlation interferogram data to an area of interest in the sample.
11. The method of claim 1, wherein the interferometer includes a reference arm and the method further comprises the step of monitoring reference arm path length, wherein the acquisition step includes the step of compensating for velocity fluctuations detected during the monitoring step.
12. The method of claim 1, further comprising the step of directing an intense pump laser to the sample, whereby the revealed backscattering characteristics will contain features corresponding to inelastic backscattering characteristics of the scatterers within the sample.
13. A method for determining depth-resolved backscatter characteristics of scatterers within a sample, comprising the steps of:
acquiring auto-correlation data from a low-coherence source interferometer, the low-coherence source interferometer including a sample arm;
acquiring multiple cross-correlation data from the low-coherence source interferometer, wherein the low-coherence source interferometer includes a sample in its sample arm;
obtaining an auto-power spectrum for a windowed portion of the auto-correlation data;
obtaining a cross-power spectrum for a windowed portion of each cross-correlation data;
obtaining a transfer function for each cross-correlation data by taking a ratio of the windowed cross-power spectrum to the auto-power spectrum;
squaring each transfer function; and
averaging the magnitude of the squared transfer functions.
14. An optical coherence tomography system comprising:
an interferometer including an optical radiation source and a sample arm, the interferometer generating a plurality of cross-correlation data outputs for a sample in the sample arm; and
a data processing system, operatively coupled to an output of the interferometer, averaging the cross-correlation data outputs, in the Fourier domain, to reveal backscattering characteristics of scatterers within the sample.
15. The optical coherence tomography system of claim 14, further comprising a database containing control data for comparison against the backscattering characteristics of scatterers within the sample.
16. A method for obtaining optical spectroscopic information from cross-correlation data obtained using low coherence interferometry, comprising:
analyzing cross-correlation data to extract spectral information about a sample,
said analyzing comprising performing a time-frequency analysis of the cross-correlation data, and
directing an intense pump laser to the sample.
17. The method of claim 16, said analyzing comprising taking the Fourier transform of the cross-correlation data.
18. The method of claim 17, further comprising obtaining several sets of cross-correlation data, and said taking the Fourier transform comprising taking the Fourier transform of several of said sets, and said analyzing comprising averaging the Fourier transform results.
19. The method of claim 17, further comprising calculating a transfer function for the cross-correlation data using the Fourier transform of auto-correlation data.
20. The method of claim 16, further comprising demodulating the cross-correlation data prior to performing a time-frequency analysis of the cross-correlation data.
21. The method of claim 20, said demodulating comprising using coherent demodulation method.
22. The method of claim 16, further comprising using an interferometer to acquire cross-correlation data, wherein the interferometer includes a reference arm and a sample arm, and controlling the depth over which cross-correlation data is acquired.
23. The method of claim 22, wherein said controlling includes the step of limiting a scan length of the reference arm to an area of interest in the sample.
24. The method of claim 16, further comprising using an interferometer to acquire cross-correlation data, and windowing the cross-correlation data to an area of interest in the sample.
25. The method of claim 16, further comprising using an interferometer to acquire cross-correlation data, wherein the interferometer includes a reference arm and the method further comprises the step of monitoring reference arm path length.
26. The method of claim 25, wherein the acquiring includes the step of compensating for velocity fluctuations detected during the monitoring step.
27. The method of claim 16, said directing comprising directing laser energy to the sample such that revealed backscattering characteristics will contain features corresponding to inelastic backscattering characteristics of the scatterers within the sample.
28. The method of claim 16, further comprising directing electromagnetic energy to the sample such that revealed backscattering characteristics will contain features corresponding to inelastic backscattering characteristics of the scatterers within the sample.
29. The method of claim 16, further comprising the step of directing a pump laser to the sample to alter backscattering characteristics of the scatterers within the sample.
30. The method of claim 16, further comprising the step of directing a pump laser to the sample, whereby revealed backscattering characteristics will contain features corresponding to inelastic backscattering characteristics of the scatterers within the sample.
31. The method of claim 16, further comprising the step of directing a pump laser to the sample to alter the spectral characteristics of the sample.
32. The method of claim 16, further comprising altering the spectral characteristics of the sample.
33. The method of claim 32, wherein said altering comprises directing laser energy to the sample.
34. The method of claim 32, wherein said altering comprises effecting stimulated emission.
35. The method of claim 34, further comprising adding external dyes or contrast agents to the sample.
36. The method of claim 32, wherein said altering comprises effecting stimulated Raman scattering.
37. The method of claim 32, further comprising adding external dyes or contrast agents to the sample.
38. The method of claim 32, wherein said altering comprises at least one of stimulated emission, stimulated Raman scattering, coherent anti-Stokes Raman scattering, stimulated Brillouin scattering, stimulated Rayleigh scattering, stimulated Rayleigh-wing scattering, and four-wave mixing.
39. A method for determining depth-resolved backscatter characteristics of scatterers within a sample, comprising the steps of:
acquiring a plurality of sets of cross-correlation interferogram data using an interferometer having a sample arm with the sample in the sample arm, wherein the sample includes a distribution of scatterers therein; and
averaging, in the Fourier domain, the cross-correlation interferogram data, thereby revealing backscattering characteristics of the scatterers within the sample.
40. The method of claim 39, further comprising the step of physically altering the distribution of scatterers within the sample.
41. The method of claim 39, further comprising the step of repositioning the sample arm.
42. The method of claim 39, further comprising the step of comparing the backscattering characteristics with control data to diagnose abnormalities or disease within the sample.
43. The method of claim 42, further comprising the steps of incorporating a sample probe of the interferometer into an endoscope or surgical instrument, and scanning the endoscope or surgical instrument along a portion of a patient's gastrointestinal tract tissue to diagnose abnormalities or disease within the patient's gastrointestinal tract tissue, wherein the control data includes data corresponding to backscattering characteristics of relatively normal gastrointestinal tract tissue.
44. The method of claim 39, wherein the acquiring cross-correlation interferogram data step or the averaging step includes the step of controlling the depth over which cross-correlation interferogram data is averaged.
45. The method of claim 44, wherein the interferometer includes a reference arm and the controlling step includes the step of limiting a scan length of the reference arm to an area of interest in the sample.
46. The method of claim 44, wherein the controlling step includes the step of windowing the cross-correlation interferogram data to an area of interest in the sample.
47. The method of claim 39, wherein the interferometer includes a reference arm and the method further comprises the step of monitoring reference arm path length, wherein the acquisition step includes the step of compensating for velocity fluctuations detected during the monitoring step.
48. The method of claim 39, further comprising the step of directing an intense pump laser to the sample, whereby the revealed backscattering characteristics will contain features corresponding to inelastic backscattering characteristics of the scatterers within the sample.
49. A method of rapidly determining cross-power spectra from cross-correlation data obtained using low coherence interferometry, comprising the steps of
passing the cross-correlation data through a bank of narrow bandpass filters, and
using the output from the narrow bandpass filters as a representation or spectral estimation of cross-power spectrum.
50. The method of claim 49, said passing comprising passing demodulated cross-correlation data, and selecting the center frequency of the bank of narrow bandpass filters according to the demodulation frequency.
51. A method for obtaining information concerning a characteristic associated with a sample from cross-correlation data obtained using low coherence interferometry, comprising:
effecting spectral alterations in the sample from which the cross-correlation data is obtained, and
analyzing the cross-correlation data to extract information pertaining to the characteristic associated with the sample.
52. The method of claim 51, further comprising using at least one of dye and contrast agent to enhance said effecting.
53. The method of claim 51, said effecting comprising at least one of using stimulated emission, using stimulated Raman scattering, using coherent anti-Stokes Raman scattering, using stimulated Brillouin scattering, using stimulated Rayleigh scattering, using stimulated Rayleigh-wing scattering, and using four-wave mixing.
54. The method of claim 51, said effecting comprising directing laser energy to the sample.
55. The method of claim 54, said directing of laser energy comprising using a beam splitter to direct both low coherence interferometer light and laser energy to the sample.
56. The method of claim 54, said directing of laser energy comprising using a wavelength division multiplexer to direct both low coherence interferometer light and laser energy to the sample.
57. The method of claim 54, said effecting comprising directing a time varying incident electromagnetic energy input to the sample, and further comprising detecting light from the sample synchronously with the modulation of the incident electromagnetic energy.
58. The method of claim 54, said effecting comprising directing pulsed incident electromagnetic energy input to the sample, and further comprising detecting light from the sample using gated integration technique.
59. The method of claim 54, said effecting comprising directing pulsed incident electromagnetic energy input to the sample, and further comprising, detecting, in a timed relation to the pulsed incident electromagnetic energy, light from the sample.
60. The method of claim 59, said detecting in a timed relation comprising using gated integration technique.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110001982A1 (en) * 2009-07-06 2011-01-06 Yu-Ta Wang Optical imaging apparatus and method
US20110178409A1 (en) * 2004-02-27 2011-07-21 Optiscan Pty Ltd Optical Element

Families Citing this family (221)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19640495C2 (en) * 1996-10-01 1999-12-16 Leica Microsystems Apparatus for confocal surface measurement
US6091984A (en) * 1997-10-10 2000-07-18 Massachusetts Institute Of Technology Measuring tissue morphology
US6640124B2 (en) 1998-01-30 2003-10-28 The Schepens Eye Research Institute Imaging apparatus and methods for near simultaneous observation of directly scattered light and multiply scattered light
US6236877B1 (en) * 1998-01-30 2001-05-22 The Schepens Eye Research Institute Apparatus for near simultaneous observation of directly scattered image field and multiply scattered image field
RU2148378C1 (en) * 1998-03-06 2000-05-10 Геликонов Валентин Михайлович Device for performing optic coherent tomography, optic fiber scanning device and method for diagnosing biological tissue in vivo
US6507747B1 (en) * 1998-12-02 2003-01-14 Board Of Regents, The University Of Texas System Method and apparatus for concomitant structural and biochemical characterization of tissue
US6404497B1 (en) 1999-01-25 2002-06-11 Massachusetts Institute Of Technology Polarized light scattering spectroscopy of tissue
US6229617B1 (en) * 1999-02-04 2001-05-08 The Regents Of The University Of California High resolution non-contact interior profilometer
US6868371B1 (en) * 1999-05-03 2005-03-15 General Electric Company System and method to quantify appearance defects in molded plastic parts
JP2001046321A (en) * 1999-08-09 2001-02-20 Asahi Optical Co Ltd Endoscope device
US6545761B1 (en) * 1999-11-30 2003-04-08 Veeco Instruments, Inc. Embedded interferometer for reference-mirror calibration of interferometric microscope
JP3999437B2 (en) * 2000-03-10 2007-10-31 富士フイルム株式会社 Optical tomograph
JP2001299676A (en) * 2000-04-25 2001-10-30 Fuji Photo Film Co Ltd Method and system for detecting sentinel lymph node
US8679089B2 (en) 2001-05-21 2014-03-25 Michael S. Berlin Glaucoma surgery methods and systems
US9603741B2 (en) 2000-05-19 2017-03-28 Michael S. Berlin Delivery system and method of use for the eye
AT377404T (en) 2000-05-19 2007-11-15 Michael S Berlin Laser application system and method for use in the eye
US6611339B1 (en) 2000-06-09 2003-08-26 Massachusetts Institute Of Technology Phase dispersive tomography
EP1210564B1 (en) * 2000-07-07 2006-08-23 Robert Bosch Gmbh Interferometric measuring device
US8909325B2 (en) 2000-08-21 2014-12-09 Biosensors International Group, Ltd. Radioactive emission detector equipped with a position tracking system and utilization thereof with medical systems and in medical procedures
US7826889B2 (en) 2000-08-21 2010-11-02 Spectrum Dynamics Llc Radioactive emission detector equipped with a position tracking system and utilization thereof with medical systems and in medical procedures
US8489176B1 (en) 2000-08-21 2013-07-16 Spectrum Dynamics Llc Radioactive emission detector equipped with a position tracking system and utilization thereof with medical systems and in medical procedures
US8565860B2 (en) 2000-08-21 2013-10-22 Biosensors International Group, Ltd. Radioactive emission detector equipped with a position tracking system
US9040016B2 (en) 2004-01-13 2015-05-26 Biosensors International Group, Ltd. Diagnostic kit and methods for radioimaging myocardial perfusion
WO2004042546A1 (en) 2002-11-04 2004-05-21 V-Target Technologies Ltd. Apparatus and methods for imaging and attenuation correction
WO2002021074A2 (en) 2000-09-04 2002-03-14 Forskningscenter Risø Optical amplification in coherence reflectometry
JP2002095663A (en) * 2000-09-26 2002-04-02 Fuji Photo Film Co Ltd Method of acquiring optical tomographic image of sentinel lymph node and its device
DE10053154B4 (en) * 2000-10-26 2011-02-17 Carl Zeiss Meditec Ag Optical coherence interferometry and coherence tomography with multiply teilhärenten light sources
EP1434522B1 (en) 2000-10-30 2010-01-13 The General Hospital Corporation Optical systems for tissue analysis
US9295391B1 (en) 2000-11-10 2016-03-29 The General Hospital Corporation Spectrally encoded miniature endoscopic imaging probe
CA2435205A1 (en) 2001-01-22 2002-08-01 V-Target Technologies Ltd. Ingestible device
US8036731B2 (en) 2001-01-22 2011-10-11 Spectrum Dynamics Llc Ingestible pill for diagnosing a gastrointestinal tract
US7450618B2 (en) 2001-01-30 2008-11-11 Board Of Trustees Operating Michigan State University Laser system using ultrashort laser pulses
US8208505B2 (en) 2001-01-30 2012-06-26 Board Of Trustees Of Michigan State University Laser system employing harmonic generation
US7583710B2 (en) 2001-01-30 2009-09-01 Board Of Trustees Operating Michigan State University Laser and environmental monitoring system
US7973936B2 (en) 2001-01-30 2011-07-05 Board Of Trustees Of Michigan State University Control system and apparatus for use with ultra-fast laser
US7567596B2 (en) 2001-01-30 2009-07-28 Board Of Trustees Of Michigan State University Control system and apparatus for use with ultra-fast laser
US6570659B2 (en) * 2001-03-16 2003-05-27 Lightlab Imaging, Llc Broadband light source system and method and light source combiner
US6552796B2 (en) * 2001-04-06 2003-04-22 Lightlab Imaging, Llc Apparatus and method for selective data collection and signal to noise ratio enhancement using optical coherence tomography
US6842255B2 (en) * 2001-04-09 2005-01-11 Canon Kabushiki Kaisha Interferometer and interferance measurement method
GB2408797B (en) 2001-05-01 2006-09-20 Gen Hospital Corp Method and apparatus for determination of atherosclerotic plaque type by measurement of tissue optical properties
US6728571B1 (en) 2001-07-16 2004-04-27 Scimed Life Systems, Inc. Electronically scanned optical coherence tomography with frequency modulated signals
US6847454B2 (en) 2001-07-16 2005-01-25 Scimed Life Systems, Inc. Systems and methods for processing signals from an interferometer by an ultrasound console
US20030045798A1 (en) * 2001-09-04 2003-03-06 Richard Hular Multisensor probe for tissue identification
JP2003090792A (en) * 2001-09-20 2003-03-28 Fuji Photo Film Co Ltd Optical tomographic imaging apparatus
US6980299B1 (en) 2001-10-16 2005-12-27 General Hospital Corporation Systems and methods for imaging a sample
US7006231B2 (en) 2001-10-18 2006-02-28 Scimed Life Systems, Inc. Diffraction grating based interferometric systems and methods
US7453445B2 (en) * 2004-08-13 2008-11-18 E Ink Corproation Methods for driving electro-optic displays
US7557929B2 (en) 2001-12-18 2009-07-07 Massachusetts Institute Of Technology Systems and methods for phase measurements
CA2473465C (en) 2002-01-11 2011-04-05 The General Hospital Corporation Apparatus for low coherence ranging
US7747315B2 (en) * 2002-01-15 2010-06-29 Board Of Regents, The University Of Texas System Methods and compositions to reduce scattering of light during therapeutic and diagnostic imaging procedures
JP2005515472A (en) * 2002-01-18 2005-05-26 ニユートン・ラボラトリーズ・インコーポレーテツド Spectroscopic diagnostic methods and systems
US7643153B2 (en) * 2003-01-24 2010-01-05 The General Hospital Corporation Apparatus and method for ranging and noise reduction of low coherence interferometry LCI and optical coherence tomography OCT signals by parallel detection of spectral bands
US7355716B2 (en) 2002-01-24 2008-04-08 The General Hospital Corporation Apparatus and method for ranging and noise reduction of low coherence interferometry LCI and optical coherence tomography OCT signals by parallel detection of spectral bands
DE10207733B4 (en) * 2002-02-22 2006-03-23 Perkin Elmer Bodenseewerk Zweigniederlassung Der Berthold Gmbh & Co. Kg spectroscopy method
US7811825B2 (en) * 2002-04-19 2010-10-12 University Of Washington System and method for processing specimens and images for optical tomography
US20040118995A1 (en) * 2002-07-25 2004-06-24 Raul Curbelo Correction for non-linearities in FTIR photo detectors
US20040068193A1 (en) * 2002-08-02 2004-04-08 Barnes Russell H. Optical devices for medical diagnostics
US7212289B1 (en) * 2002-11-18 2007-05-01 Carl Zeiss Smt Ag Interferometric measurement device for determining the birefringence in a transparent object
WO2004058058A1 (en) * 2002-12-30 2004-07-15 Koninklijke Philips Electronics N.V. Analysis apparatus and method
US7075658B2 (en) * 2003-01-24 2006-07-11 Duke University Method for optical coherence tomography imaging with molecular contrast
US7623908B2 (en) * 2003-01-24 2009-11-24 The Board Of Trustees Of The University Of Illinois Nonlinear interferometric vibrational imaging
CN1741768A (en) 2003-01-24 2006-03-01 通用医疗有限公司 System and method for identifying tissue using low-coherence interferometry
US7429860B2 (en) * 2003-01-28 2008-09-30 University Of Southern California Noise reduction for spectroscopic signal processing
US7593763B2 (en) * 2003-02-05 2009-09-22 Childrens Hospital Los Angeles Non-invasive in vivo measurement of macular carotenoids
WO2004073501A2 (en) * 2003-02-20 2004-09-02 Gutin Mikhail Optical coherence tomography with 3d coherence scanning
CA2519937C (en) 2003-03-31 2012-11-20 Guillermo J. Tearney Speckle reduction in optical coherence tomography by path length encoded angular compounding
US7092101B2 (en) * 2003-04-16 2006-08-15 Duke University Methods and systems for static multimode multiplex spectroscopy
US7102758B2 (en) * 2003-05-06 2006-09-05 Duke University Fourier domain low-coherence interferometry for light scattering spectroscopy apparatus and method
US7376455B2 (en) * 2003-05-22 2008-05-20 Scimed Life Systems, Inc. Systems and methods for dynamic optical imaging
EP3002547B1 (en) 2003-06-06 2019-04-03 The General Hospital Corporation Process and apparatus for a wavelength tuning source
US20050018944A1 (en) * 2003-07-25 2005-01-27 Mozdy Eric J. Polarization modulation interrogation of grating-coupled waveguide sensors
EP2278287B1 (en) 2003-10-27 2016-09-07 The General Hospital Corporation Method and apparatus for performing optical imaging using frequency-domain interferometry
US7610074B2 (en) * 2004-01-08 2009-10-27 The Board Of Trustees Of The University Of Illinois Multi-functional plasmon-resonant contrast agents for optical coherence tomography
US9470801B2 (en) 2004-01-13 2016-10-18 Spectrum Dynamics Llc Gating with anatomically varying durations
US8423125B2 (en) 2004-11-09 2013-04-16 Spectrum Dynamics Llc Radioimaging
US7968851B2 (en) 2004-01-13 2011-06-28 Spectrum Dynamics Llc Dynamic spect camera
EP1709585A4 (en) 2004-01-13 2015-11-25 Biosensors Int Group Ltd Multi-dimensional image reconstruction
US8586932B2 (en) 2004-11-09 2013-11-19 Spectrum Dynamics Llc System and method for radioactive emission measurement
US9316743B2 (en) 2004-11-09 2016-04-19 Biosensors International Group, Ltd. System and method for radioactive emission measurement
US7872235B2 (en) 2005-01-13 2011-01-18 Spectrum Dynamics Llc Multi-dimensional image reconstruction and analysis for expert-system diagnosis
WO2006051531A2 (en) 2004-11-09 2006-05-18 Spectrum Dynamics Llc Radioimaging
US9943274B2 (en) 2004-11-09 2018-04-17 Spectrum Dynamics Medical Limited Radioimaging using low dose isotope
FR2870004B1 (en) * 2004-05-04 2006-07-28 Thales Sa Device for measuring low-cost frequency shift by Doppler effect
US7327463B2 (en) 2004-05-14 2008-02-05 Medrikon Corporation Low coherence interferometry utilizing magnitude
US7190464B2 (en) 2004-05-14 2007-03-13 Medeikon Corporation Low coherence interferometry for detecting and characterizing plaques
US7474408B2 (en) 2004-05-14 2009-01-06 Medeikon Corporation Low coherence interferometry utilizing phase
US7184148B2 (en) 2004-05-14 2007-02-27 Medeikon Corporation Low coherence interferometry utilizing phase
US7242480B2 (en) 2004-05-14 2007-07-10 Medeikon Corporation Low coherence interferometry for detecting and characterizing plaques
WO2005112895A2 (en) 2004-05-20 2005-12-01 Spectrum Dynamics Llc Ingestible device platform for the colon
WO2005117534A2 (en) 2004-05-29 2005-12-15 The General Hospital Corporation Process, system and software arrangement for a chromatic dispersion compensation using reflective layers in optical coherence tomography (oct) imaging
EP1778957A4 (en) 2004-06-01 2015-12-23 Biosensors Int Group Ltd Radioactive-emission-measurement optimization to specific body structures
US8280124B2 (en) 2004-06-01 2012-10-02 Spectrum Dynamics Llc Methods of view selection for radioactive emission measurements
US7796243B2 (en) * 2004-06-09 2010-09-14 National Research Council Of Canada Detection and monitoring of changes in mineralized tissues or calcified deposits by optical coherence tomography and Raman spectroscopy
WO2006014392A1 (en) 2004-07-02 2006-02-09 The General Hospital Corporation Endoscopic imaging probe comprising dual clad fibre
JP5053845B2 (en) 2004-08-06 2012-10-24 ザ ジェネラル ホスピタル コーポレイション The method for determining at least one position in a sample using optical coherence tomography, system and software device
EP2272420B1 (en) 2004-08-24 2013-06-19 The General Hospital Corporation Apparatus for imaging of vessel segments
AT538714T (en) 2004-08-24 2012-01-15 Gen Hospital Corp Method, system and software arrangement for determining the elasticity module
EP2302364A3 (en) 2004-09-10 2011-04-06 The General Hospital Corporation System and method for optical coherence imaging
EP2329759B1 (en) 2004-09-29 2014-03-12 The General Hospital Corporation System and method for optical coherence imaging
JP4566685B2 (en) * 2004-10-13 2010-10-20 株式会社トプコン The optical image measurement device and an optical image measuring method
JP4494160B2 (en) 2004-10-14 2010-06-30 株式会社トプコン The optical image measurement device
US8571881B2 (en) 2004-11-09 2013-10-29 Spectrum Dynamics, Llc Radiopharmaceutical dispensing, administration, and imaging
US8615405B2 (en) 2004-11-09 2013-12-24 Biosensors International Group, Ltd. Imaging system customization using data from radiopharmaceutical-associated data carrier
WO2007010534A2 (en) 2005-07-19 2007-01-25 Spectrum Dynamics Llc Imaging protocols
EP1952180B1 (en) 2005-11-09 2017-01-04 Biosensors International Group, Ltd. Dynamic spect camera
US8837793B2 (en) 2005-07-19 2014-09-16 Biosensors International Group, Ltd. Reconstruction stabilizer and active vision
WO2007010537A2 (en) 2005-07-19 2007-01-25 Spectrum Dynamics Llc Reconstruction stabilizer and active vision
EP2278265A3 (en) 2004-11-24 2011-06-29 The General Hospital Corporation Common-Path Interferometer for Endoscopic OCT
WO2006058346A1 (en) 2004-11-29 2006-06-01 The General Hospital Corporation Arrangements, devices, endoscopes, catheters and methods for performing optical imaging by simultaneously illuminating and detecting multiple points on a sample
US7336366B2 (en) * 2005-01-20 2008-02-26 Duke University Methods and systems for reducing complex conjugate ambiguity in interferometric data
EP1851532A1 (en) * 2005-02-14 2007-11-07 Board of Trustees of Michigan State University Ultra-fast laser system
US7586618B2 (en) * 2005-02-28 2009-09-08 The Board Of Trustees Of The University Of Illinois Distinguishing non-resonant four-wave-mixing noise in coherent stokes and anti-stokes Raman scattering
US7493227B2 (en) 2005-03-17 2009-02-17 The Board Of Trustees Of The Leland Stanford Junior University Method for determining the complex scattering function of an optical coherence tomography sample
US7369953B2 (en) * 2005-03-17 2008-05-06 The Board Of Trustees Of The Leland Stanford Junior University Femtosecond spectroscopy using minimum phase functions
US7643952B2 (en) 2005-04-05 2010-01-05 The Board Of Trustees Of The Leland Stanford Junior University Optical image processing using minimum phase functions
US7725169B2 (en) 2005-04-15 2010-05-25 The Board Of Trustees Of The University Of Illinois Contrast enhanced spectroscopic optical coherence tomography
ES2337497T3 (en) 2005-04-28 2010-04-26 The General Hospital Corporation Evaluation of characteristics of the image of an anatomical structure images of optical coherence tomography.
EP1887926B1 (en) * 2005-05-31 2014-07-30 The General Hospital Corporation System and method which use spectral encoding heterodyne interferometry techniques for imaging
EP1889037A2 (en) 2005-06-01 2008-02-20 The General Hospital Corporation Apparatus, method and system for performing phase-resolved optical frequency domain imaging
CN101238347B (en) 2005-08-09 2011-05-25 通用医疗公司 Apparatus, methods and storage medium for performing polarization-based quadrature demodulation in optical coherence tomography
DE102006016132A1 (en) * 2005-09-22 2007-03-29 Robert Bosch Gmbh Interferometric measuring apparatus for measuring multiple layer structures using optimal selection of the input beam length
DE102006016131A1 (en) * 2005-09-22 2007-03-29 Robert Bosch Gmbh Interferometric measuring device
JP2009509149A (en) * 2005-09-22 2009-03-05 ローベルト ボツシユ ゲゼルシヤフト ミツト ベシユレンクテル ハフツングRobert Bosch Gmbh The layer thickness determined by the interferometer
KR20080066705A (en) 2005-09-29 2008-07-16 더 제너럴 하스피탈 코포레이션 Method and apparatus for method for viewing and analyzing of one or more biological smaples with progressively increasing resolutions
US8537366B2 (en) 2005-10-11 2013-09-17 Duke University Systems and methods for endoscopic angle-resolved low coherence interferometry
CN101326428B (en) 2005-10-11 2011-05-18 杜克大学 Systems and method for endoscopic angle-resolved low coherence interferometry
JP5203951B2 (en) 2005-10-14 2013-06-05 ザ ジェネラル ホスピタル コーポレイション Spectrum and frequency encoding fluorescent imaging
EP1957959A2 (en) 2005-11-30 2008-08-20 Board of Trustees of Michigan State University Laser based identification of molecular characteristics
WO2007074466A2 (en) 2005-12-28 2007-07-05 Starhome Gmbh Late forwarding to local voicemail system of calls to roaming users
EP1971848A1 (en) 2006-01-10 2008-09-24 The General Hospital Corporation Systems and methods for generating data based on one or more spectrally-encoded endoscopy techniques
US8145018B2 (en) 2006-01-19 2012-03-27 The General Hospital Corporation Apparatus for obtaining information for a structure using spectrally-encoded endoscopy techniques and methods for producing one or more optical arrangements
WO2007084995A2 (en) 2006-01-19 2007-07-26 The General Hospital Corporation Methods and systems for optical imaging of epithelial luminal organs by beam scanning thereof
AU2007211061B2 (en) 2006-01-31 2013-04-18 The Board Of Trustees Of The University Of Illinois Method and apparatus for measurement of optical properties in tissue
EP2659852A3 (en) 2006-02-01 2014-01-15 The General Hospital Corporation Apparatus for applying a plurality of electro-magnetic radiations to a sample
JP5519152B2 (en) * 2006-02-08 2014-06-11 ザ ジェネラル ホスピタル コーポレイション Apparatus for acquiring information related to anatomical sample using optical microscopy
US20070239031A1 (en) * 2006-02-15 2007-10-11 Kye-Sung Lee Systems and methods for performing simultaneous tomography and spectroscopy
JP2009527770A (en) 2006-02-24 2009-07-30 ザ ジェネラル ホスピタル コーポレイション Angle-resolved Fourier domain optical coherence tomography performing method and system
EP2004041B1 (en) 2006-04-05 2013-11-06 The General Hospital Corporation Methods, arrangements and systems for polarization-sensitive optical frequency domain imaging of a sample
WO2007145702A2 (en) 2006-04-10 2007-12-21 Board Of Trustees Of Michigan State University Laser material processing systems and methods with, in particular, use of a hollow waveguide for broadening the bandwidth of the pulse above 20 nm
EP2015669A2 (en) 2006-05-10 2009-01-21 The General Hospital Corporation Processes, arrangements and systems for providing frequency domain imaging of a sample
US8894974B2 (en) 2006-05-11 2014-11-25 Spectrum Dynamics Llc Radiopharmaceuticals for diagnosis and therapy
WO2007133964A2 (en) * 2006-05-12 2007-11-22 The General Hospital Corporation Processes, arrangements and systems for providing a fiber layer thickness map based on optical coherence tomography images
US7488930B2 (en) 2006-06-02 2009-02-10 Medeikon Corporation Multi-channel low coherence interferometer
WO2008011580A2 (en) * 2006-07-21 2008-01-24 Oncoscope, Inc. Protective probe tip, particularly for use on a fiber-optic probe used in an endoscopic application
EP3006920A3 (en) 2006-08-25 2016-08-03 The General Hospital Corporation Apparatus and methods for enhancing optical coherence tomography imaging using volumetric filtering techniques
WO2008049118A2 (en) 2006-10-19 2008-04-24 The General Hospital Corporation Apparatus and method for obtaining and providing imaging information associated with at least one portion of a sample and effecting such portion(s)
CN100464692C (en) 2006-11-09 2009-03-04 上海理工大学 A method and an apparatus for obtaining tissue micro tomography images and spectrums
US8610075B2 (en) 2006-11-13 2013-12-17 Biosensors International Group Ltd. Radioimaging applications of and novel formulations of teboroxime
WO2008075362A2 (en) 2006-12-20 2008-06-26 Spectrum Dynamics Llc A method, a system, and an apparatus for using and processing multidimensional data
EP2662674A3 (en) 2007-01-19 2014-06-25 The General Hospital Corporation Rotating disk reflection for fast wavelength scanning of dispersed broadbend light
WO2008089406A2 (en) 2007-01-19 2008-07-24 The General Hospital Corporation Apparatus and method for simultaneous inspection at different depths based on the principle of frequency domain optical coherence tomography
EP2132840A2 (en) 2007-03-23 2009-12-16 The General Hospital Corporation Methods, arrangements and apparatus for utlizing a wavelength-swept laser using angular scanning and dispersion procedures
US8045177B2 (en) 2007-04-17 2011-10-25 The General Hospital Corporation Apparatus and methods for measuring vibrations using spectrally-encoded endoscopy
US8115919B2 (en) 2007-05-04 2012-02-14 The General Hospital Corporation Methods, arrangements and systems for obtaining information associated with a sample using optical microscopy
US7929134B2 (en) * 2007-05-25 2011-04-19 Case Western Reserve University Even frequency spacing spectrometer and optical coherence tomography device
EP2160217A1 (en) * 2007-06-08 2010-03-10 Prescient Medical, Inc. Optical catheter configurations combining raman spectroscopy with optical fiber-based low coherence reflectometry
US7508524B2 (en) * 2007-07-20 2009-03-24 Vanderbilt University Combined raman spectroscopy-optical coherence tomography (RS-OCT) system and applications of the same
WO2009018456A2 (en) 2007-07-31 2009-02-05 The General Hospital Corporation Systems and methods for providing beam scan patterns for high speed doppler optical frequency domain imaging
JP5536650B2 (en) 2007-08-31 2014-07-02 ザ ジェネラル ホスピタル コーポレイション System and method for self-interference fluorescence microscopy, and computer-accessible medium associated therewith
AU2008298551A1 (en) * 2007-09-13 2009-03-19 Duke University Apparatuses, systems, and methods for low-coherence interferometry (LCI)
US8521253B2 (en) 2007-10-29 2013-08-27 Spectrum Dynamics Llc Prostate imaging
WO2009059034A1 (en) 2007-10-30 2009-05-07 The General Hospital Corporation System and method for cladding mode detection
JP5002429B2 (en) * 2007-11-20 2012-08-15 テルモ株式会社 Optical coherent tomography diagnosis apparatus
US8218152B1 (en) * 2007-12-04 2012-07-10 The Board Of Trustees Of The University Of Illinois Group refractive index reconstruction with broadband interferometric confocal microscopy
US8311069B2 (en) 2007-12-21 2012-11-13 Board Of Trustees Of Michigan State University Direct ultrashort laser system
US20090177094A1 (en) * 2008-01-08 2009-07-09 Oncoscope, Inc. Systems and methods for tissue examination, diagnostic, treatment, and/or monitoring
US8115934B2 (en) 2008-01-18 2012-02-14 The Board Of Trustees Of The University Of Illinois Device and method for imaging the ear using optical coherence tomography
US7751057B2 (en) 2008-01-18 2010-07-06 The Board Of Trustees Of The University Of Illinois Magnetomotive optical coherence tomography
US8983580B2 (en) 2008-01-18 2015-03-17 The Board Of Trustees Of The University Of Illinois Low-coherence interferometry and optical coherence tomography for image-guided surgical treatment of solid tumors
US9332942B2 (en) 2008-01-28 2016-05-10 The General Hospital Corporation Systems, processes and computer-accessible medium for providing hybrid flourescence and optical coherence tomography imaging
US7884946B2 (en) * 2008-04-28 2011-02-08 Lumetrics, Inc. Apparatus for measurement of the axial length of an eye
WO2009137701A2 (en) 2008-05-07 2009-11-12 The General Hospital Corporation System, method and computer-accessible medium for tracking vessel motion during three-dimensional coronary artery microscopy
JP5268425B2 (en) * 2008-05-16 2013-08-21 キヤノン株式会社 Profilometer and an exposure apparatus
JP2009293998A (en) * 2008-06-03 2009-12-17 Shofu Inc Interference tomographic photographing apparatus
EP2335030A4 (en) * 2008-06-18 2014-05-07 Eyelab Group Llc System and method for determining volume-related parameters of ocular and other biological tissues
JP5795531B2 (en) 2008-06-20 2015-10-14 ザ ジェネラル ホスピタル コーポレイション Fused fiber optic coupler structure, and methods of use thereof
EP2309923A4 (en) 2008-07-14 2015-03-18 Gen Hospital Corp Apparatus and methods for color endoscopy
EP3330696A1 (en) 2008-12-10 2018-06-06 The General Hospital Corporation Systems, apparatus and methods for extending imaging depth range of optical coherence tomography through optical sub-sampling
JP5602363B2 (en) * 2008-12-26 2014-10-08 キヤノン株式会社 Optical coherence tomography apparatus
US8675699B2 (en) 2009-01-23 2014-03-18 Board Of Trustees Of Michigan State University Laser pulse synthesis system
EP2382456A4 (en) 2009-01-26 2012-07-25 Gen Hospital Corp System, method and computer-accessible medium for providing wide-field superresolution microscopy
WO2010091190A2 (en) 2009-02-04 2010-08-12 The General Hospital Corporation Apparatus and method for utilization of a high-speed optical wavelength tuning source
WO2010141128A2 (en) 2009-03-05 2010-12-09 Board Of Trustees Of Michigan State University Laser amplification system
US9351642B2 (en) 2009-03-12 2016-05-31 The General Hospital Corporation Non-contact optical system, computer-accessible medium and method for measurement at least one mechanical property of tissue using coherent speckle technique(s)
US8264694B2 (en) * 2009-03-16 2012-09-11 Ut-Battelle, Llc Quantitative phase-contrast and excitation-emission systems
US8248614B2 (en) * 2009-03-16 2012-08-21 Ut-Battelle, Llc Quantitative phase-imaging systems
FR2945629B1 (en) * 2009-05-15 2011-06-10 Formulaction Method for rheological characterization of a complex environment
US8338788B2 (en) 2009-07-29 2012-12-25 Spectrum Dynamics Llc Method and system of optimized volumetric imaging
US9823127B2 (en) 2010-01-22 2017-11-21 Duke University Systems and methods for deep spectroscopic imaging of biological samples with use of an interferometer and spectrometer
AU2011207444A1 (en) 2010-01-22 2012-08-09 Duke University Multiple window processing schemes for spectroscopic optical coherence tomography (OCT) and fourier domain low coherence interferometry
US8630322B2 (en) 2010-03-01 2014-01-14 Board Of Trustees Of Michigan State University Laser system for output manipulation
EP2542154A4 (en) 2010-03-05 2014-05-21 Gen Hospital Corp Systems, methods and computer-accessible medium which provide microscopic images of at least one anatomical structure at a particular resolution
US20130107269A1 (en) * 2010-03-17 2013-05-02 National University Corporation Nagaoka University Of Technology Electric field spectrum measurement device and object measurement device
WO2011127584A1 (en) * 2010-04-13 2011-10-20 University Of Manitoba Methods and systems for use in imaging using interferometry
US9069130B2 (en) 2010-05-03 2015-06-30 The General Hospital Corporation Apparatus, method and system for generating optical radiation from biological gain media
JP5778762B2 (en) 2010-05-25 2015-09-16 ザ ジェネラル ホスピタル コーポレイション Apparatus and method for spectral analysis of optical coherence tomography images
WO2011149972A2 (en) 2010-05-25 2011-12-01 The General Hospital Corporation Systems, devices, methods, apparatus and computer-accessible media for providing optical imaging of structures and compositions
EP2575591A4 (en) 2010-06-03 2017-09-13 The General Hospital Corporation Apparatus and method for devices for imaging structures in or at one or more luminal organs
US9510758B2 (en) 2010-10-27 2016-12-06 The General Hospital Corporation Apparatus, systems and methods for measuring blood pressure within at least one vessel
DE102011018603B3 (en) * 2011-04-21 2012-06-06 Medizinisches Laserzentrum Lübeck GmbH A method for optical tomography
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US10072920B2 (en) * 2015-05-22 2018-09-11 Cornell University Optical sensing based on measurements of displacements induced by optical scattering forces in viscoelastic media using phase-sensitive optical coherence tomography
WO2018160874A1 (en) * 2017-03-01 2018-09-07 University Of Maryland, College Park Cell classification based on mechanical signature of nucleus

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4063549A (en) 1975-12-22 1977-12-20 Technicon Instruments Corporation Ultrasonic method and apparatus for imaging and characterization of bodies
US5158090A (en) 1989-11-16 1992-10-27 Chemnitz Technische Universitaet Method and arrangement for depicting structures
US5200819A (en) 1988-05-27 1993-04-06 The University Of Connecticut Multi-dimensional imaging system for endoscope
US5204734A (en) * 1991-06-12 1993-04-20 Wyko Corporation Rough surface profiler and method
US5353802A (en) 1990-10-18 1994-10-11 Centrum For Dentalteknik Och Biomaterial Device for measurement of electrical impedance of organic and biological materials
US5459570A (en) 1991-04-29 1995-10-17 Massachusetts Institute Of Technology Method and apparatus for performing optical measurements
US5491524A (en) 1994-10-05 1996-02-13 Carl Zeiss, Inc. Optical coherence tomography corneal mapping apparatus
US5493109A (en) 1994-08-18 1996-02-20 Carl Zeiss, Inc. Optical coherence tomography assisted ophthalmologic surgical microscope
US5501226A (en) 1994-10-19 1996-03-26 Carl Zeiss, Inc. Short coherence length, doppler velocimetry system
US5565986A (en) 1994-03-30 1996-10-15 Kn+E,Uml U+Ee Ttel; Alexander Stationary optical spectroscopic imaging in turbid objects by special light focusing and signal detection of light with various optical wavelengths
US5644642A (en) 1995-04-03 1997-07-01 Carl Zeiss, Inc. Gaze tracking using optical coherence tomography
US5994690A (en) * 1997-03-17 1999-11-30 Kulkarni; Manish D. Image enhancement in optical coherence tomography using deconvolution
WO2000069333A1 (en) 1999-05-19 2000-11-23 The Regents Of The University Of California Optical detection of dental disease using polarized light

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4063549A (en) 1975-12-22 1977-12-20 Technicon Instruments Corporation Ultrasonic method and apparatus for imaging and characterization of bodies
US5200819A (en) 1988-05-27 1993-04-06 The University Of Connecticut Multi-dimensional imaging system for endoscope
US5158090A (en) 1989-11-16 1992-10-27 Chemnitz Technische Universitaet Method and arrangement for depicting structures
US5353802A (en) 1990-10-18 1994-10-11 Centrum For Dentalteknik Och Biomaterial Device for measurement of electrical impedance of organic and biological materials
US5459570A (en) 1991-04-29 1995-10-17 Massachusetts Institute Of Technology Method and apparatus for performing optical measurements
US5204734A (en) * 1991-06-12 1993-04-20 Wyko Corporation Rough surface profiler and method
US5565986A (en) 1994-03-30 1996-10-15 Kn+E,Uml U+Ee Ttel; Alexander Stationary optical spectroscopic imaging in turbid objects by special light focusing and signal detection of light with various optical wavelengths
US5493109A (en) 1994-08-18 1996-02-20 Carl Zeiss, Inc. Optical coherence tomography assisted ophthalmologic surgical microscope
US5491524A (en) 1994-10-05 1996-02-13 Carl Zeiss, Inc. Optical coherence tomography corneal mapping apparatus
US5501226A (en) 1994-10-19 1996-03-26 Carl Zeiss, Inc. Short coherence length, doppler velocimetry system
US5549114A (en) 1994-10-19 1996-08-27 Carl Zeiss, Inc. Short coherence length, doppler velocimetry system
US5644642A (en) 1995-04-03 1997-07-01 Carl Zeiss, Inc. Gaze tracking using optical coherence tomography
US5994690A (en) * 1997-03-17 1999-11-30 Kulkarni; Manish D. Image enhancement in optical coherence tomography using deconvolution
WO2000069333A1 (en) 1999-05-19 2000-11-23 The Regents Of The University Of California Optical detection of dental disease using polarized light

Non-Patent Citations (22)

* Cited by examiner, † Cited by third party
Title
A. Papoulis, Systems and Transforms with Applications in Optics. pp. 254-293. McGraw-Hill Book Company (1968).
Boer De J.F. et al: "Polarization Effects in Optical Coherence Tomography of Various Biological Tissues", IEEE Journal of Selected Topics in Quantum Electronics, IEEE Service Center, US., vol. 5, No. 4, Jul. 1999, pp. 1200-1203, XP00893469, Chapter III, pp. 1200-1201, Figure 1.
Correlations of Acoustic Tissue Typing of Malignant Melanoma and Histopathologic Features as a Predictor of Death, D. J. Coleman et al., American Journal of Opthalmology, 110:380-388 (Oct. 1990).
D. Huang et al., Optical Coherence Tomography, Science, vol. 254, pp. 1178-1181 (Nov. 22, 1991).
Detection of gastrointestinal cancer by elastic scattering and absorption spectroscopies with the Los Alamos Optical Biopsy System, Progress in Biomedical Optics: Proceedings of Advances in Laser and Light Spectroscopy to Diagnose Cancer and Other Disease II, San Jose, CA (Feb. 7-8, 1995).
Diagnostic Spectrum Analysis in Ophthalmology: A Physical Perspective, E.J. Feleppa, Ultrasound in Med. & Biol. vol. 12, No, 8 (1986).
Everett M.J. et al:"Non-invasive Diagnosis Of Early Caries With Polarization Sensitive Optical Coherence Tomography", Proceedings of the SPIE, SPIE, Bellingham, VA, us, vol. 3593, Jan. 24, 1999, pp. 177-182, XP000931184, Chapter 3, pp. 178-179, Figure 1.
J. Izat et al., Micron-Resolution Biomedical Imaging with Optical Coherence Tomography. Optice & Photonics News (Oct. 1993).
J.M. Mendel, Maximum-Likelihood Deconvolution, A Journey into Model-Based Signal Processing. Springer-Verlag New York Inc., pp. 1-77 (1990).
M. Siddique et al., Time-Resolved studies of stimulated emission from colloidal dye solutions. Optics Letters, vol. 21. No. 7 (Apr. 1, 1996).
N.M. Lawandy et al., Laser action in strongly scattering media. Nature, vol. 368 (Mar. 31, 1994).
Noninvasive Identification of Bladder Cancer with Subsurface Backscattered Light, I.J. Bigio et al., Progress in Biomedical Optics: Proceedings of Advances in Laser and Light Spectroscopy to Diagnose Cancer and Other Diseases, Los Angeles, CA (Jan. 23-24, 1994).
P.L. Francois et al., Three Ways to Implement Interferencial Techniques: Application to Measurements of Chromatic Dispersion, Birefringence, and Nonlinear Susceptibilities. Journal of Lightware Technology, vol. 7, No. 3 (Mar. 1989).
Precise characterization of the Raman nonlinearity in benzene using nonlinear interferometry, A. Owyoung et al., Journal of Applied Physics, vol. 48, No. 2 (Feb. 1977).
R.C. Youngquist et al., Optical Coherence-Domain Reflectometry: A New Optical Evaluation Technique. Optics Letters. vol. 12. No. 3. pp. 158-160 (Mar. 1997) .
R.M. Balachandra et al., Laser action in polymeric gain media containing scattering particles. Applied Optics, vol. 35, No. 4 (Feb. 1, 1996).
Rapid Near-Infrared Raman Spectroscopy of Human Tissue with a Spectrograph and CCD Detector, J.J. Baraga, Applied Spectroscopy, vol. 46, No. 2 (1992).
Simultaneous Measurement of Dispersion, Spectrum, and Distance with a Fourier Transform Spectrometer, T. Hellmuth et al., Journal of Biomedical Optics, vol. 3, No. 1 (Jan. 1998).
Spectroscopic optical coherence tomography, M.D. Kulkarni et al., Conference on Lasers and Electro-Optics, vol. 9 1996 Technical Digest Series Conference Edition (Jun. 2-7, 1996).
Theoretical and Experimental Investigations of Elastic Scattering Spectroscopy as a Potential Diagnostic for Tissue Pathologies, J. Boyer et al., OSA Proceedings on Advances in Optical Imaging and Photon Migration, vol. 21, Orlando, FL (Mar. 21-23, 1994).
Theoretical framework for spectrum analysis in ultrasonic tissue characterization, F.L. Lizzi et al., J. Acoust. Soc. Am., 73 (4) (Apr. 1983).
Ultrasonic Tissue Characterizationof Uveal Melanoma and Prediction of Patient Survival After Enucleation and Brachytherapy, D.J. Coleman et al., American Journal of Opthalmology, 112:682-688 (Dec. 1991).

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110178409A1 (en) * 2004-02-27 2011-07-21 Optiscan Pty Ltd Optical Element
US20110001982A1 (en) * 2009-07-06 2011-01-06 Yu-Ta Wang Optical imaging apparatus and method
US8493568B2 (en) * 2009-07-06 2013-07-23 National Taiwan University Optical imaging apparatus and method

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