WO2007115200A2 - Procede et systeme pour une detection adaptative et robuste - Google Patents

Procede et systeme pour une detection adaptative et robuste Download PDF

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Publication number
WO2007115200A2
WO2007115200A2 PCT/US2007/065680 US2007065680W WO2007115200A2 WO 2007115200 A2 WO2007115200 A2 WO 2007115200A2 US 2007065680 W US2007065680 W US 2007065680W WO 2007115200 A2 WO2007115200 A2 WO 2007115200A2
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peak
pulse
waveform
thermoacoustic
tissue
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PCT/US2007/065680
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WO2007115200A3 (fr
Inventor
Yao Xie
Bin Guo
Jian Li
Geng Ku
Lihong Wang
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University Of Florida Research Foundation, Inc.
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Publication of WO2007115200A3 publication Critical patent/WO2007115200A3/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0093—Detecting, measuring or recording by applying one single type of energy and measuring its conversion into another type of energy
    • A61B5/0095—Detecting, measuring or recording by applying one single type of energy and measuring its conversion into another type of energy by applying light and detecting acoustic waves, i.e. photoacoustic measurements
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A61B5/0091—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for mammography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
    • A61B5/4306—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the female reproductive systems, e.g. gynaecological evaluations
    • A61B5/4312—Breast evaluation or disorder diagnosis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/1702—Systems in which incident light is modified in accordance with the properties of the material investigated with opto-acoustic detection, e.g. for gases or analysing solids

Definitions

  • the present invention relates to the field of imaging, and more particularly, to image reconstruction.
  • TAT Thermoacoustic tomography
  • Thermoacoustic tomography applies to a wide span of biomedical applications.
  • the physical basis of TAT lies in the contrast of the radiation absorption rate among different biological tissues. Due to the thermoacoustic effect, when a short electromagnetic pulse, such as microwave or laser, is absorbed by a tissue, the heating results in expansion of tissue that generates acoustic signals.
  • a short electromagnetic pulse such as microwave or laser
  • TAT an image of the tissue absorption properties can be reconstructed from the recorded thermoacoustic signals. The image reveals the physiological and pathological state of the tissue.
  • TAT has been used in many applications including breast cancer detection.
  • TAT provides both enhanced imaging resolution and good spatial contrast properties.
  • microwave imaging offers excellent contrast between cancerous and normal breast tissue, but the relatively long wavelengths of microwaves provide poor spatial resolution.
  • conventional ultrasound imaging has very fine spatial resolution, but poor soft tissue contrast.
  • microwave-induced TAT takes advantage of both the high contrast of biological tissue in electromagnetic frequency band (microwave) and the millimeter range spatial resolution due to the acoustic signals (ultrasound) used in image reconstruction.
  • DAS delay-And-sum
  • image reconstruction using DAS requires minimal prior information on the tissue for image reconstruction. Consequently, DAS can be a fast and straightforward technique for processing wideband acoustic signals.
  • DAS algorithms can provide image qualities comparable to those of exact reconstruction algorithms.
  • these data- independent methods tend to suffer from poor resolution, high sidelobe level problems, and poor interference rejection capabilities.
  • TAT Distortion issues in TAT are different from that in UT.
  • amplitude distortion caused by refraction can be more problematic than phase distortion induced by acoustic speed variation.
  • phase distortion dominates amplitude distortion.
  • the invention relates generally to a system and method for adaptive and robust detection of thermoacoustic signals for high contrast and high resolution imaging in TAT.
  • the signal processing principles of operation can be applied to other forms of imaging such as ultrasound imaging and microwave imaging, and are not limited to thermoacoustic imaging.
  • thermoacoustic signal can include a pulse component and a noise component, both generated as a result of radiation absorption.
  • a waveform of the pulse component can be estimated by applying RCB to the multiple thermoacoustic signals. ARTs applied within the RCB can mitigate amplitude and phase distortion due to the noise component, which can include multi-path interference and variation in acoustic speed through the tissue.
  • a response intensity can be evaluated from the waveform for reconstructing an image of the thermoacoustic response intensity corresponding to an absorption property of the tissue.
  • the method can include measuring an amplitude distortion from the thermoacoustic signals, and allowing an uncertainty in the amplitude distortion of the waveform to accommodate an uncertainty range of the phase distortion.
  • the amplitude distortion may be associated with a refraction property of the tissue.
  • the phase distortion may be associated with an sound speed variation due to the tissue.
  • the method can further include searching for a peak in the uncertainty range to estimate a phase distortion, and comparing a location of the peak to an expected location.
  • a phase distortion correction can be applied to compensate the waveform for the phase distortion by shifting the waveform by the determined phase distortion.
  • the method also can include enhancing a contrast of the image by using a peak-to-peak difference for the response intensity of the focal point.
  • the waveform can be bipolar, having a positive peak corresponding to a compression pulse and a negative peak corresponding to a rarefaction pulse.
  • the response intensity can be the peak-to-peak difference of the bipolar waveform at a particular peak location.
  • the focal point can be scanned from one or more locations to cover an entire cross- section of the tissue, wherein the scanning can occur at multiple heights. [00011]
  • the response intensity of a focal point can be determined, according to one embodiment of the invention, as follows: detecting a peak; calculating an arrival time of the pulse component based on the peak; aligning one or more thermoacoustic signals based on the arrival time; and compensating for a loss in amplitude due to a propagation decay associated with the tissue.
  • the searching can be performed within an interval around the arrival time, and the interval can be determined by a difference between a true arrival time and the actual arrival time.
  • the search range can be based on an estimated variance of arrival time differences.
  • the arrival time can account for homogeneous acoustic properties of the tissue.
  • a method can include estimating an acoustic pulse generated by a focal point from one or more thermoacoustic signals using RCB, searching for a peak in the acoustic pulse for mitigating a phase aberration, and calculating a response intensity from the peak for forming one portion of an image.
  • An array steering vector can be estimated using covariance fitting.
  • An optimal beamformer weight vector can be obtained from the estimated steering vector for estimating a waveform of the pulse. The array steering vector can maximize a power of the pulse subject to a dual constraint optimization that uses the optimal beamformer weight vector.
  • a first constraint of the dual optimization can be a function of a covariance of the waveform, a power of the pulse in the waveform, and an array steering vector weighting the pulse.
  • a second constraint of the dual optimization can be an uncertainty set that is least one of a spherical uncertainty and an elliptical uncertainty.
  • the uncertainty set allows the array steering vector to accommodate an uncertainty range during a phase measurement.
  • a peak can be searched within the extended uncertainty range for mitigating phase distortions.
  • the error bound can be a user-provided parameter for adjusting a resolution and a contrast of the image. For example, a smaller error can provide an increased ability of the RCB to suppress interference that is close to the pulse for increasing a resolution of the image.
  • a larger error can provide an increased robustness of the RCB to tolerate distortions due to a small sample size of thermoacoustic signals.
  • the uncertainty set can be decreased for images having low resolution, and increased for images distorted by interference.
  • a Lagrange multiplier can be employed within the dual constraint optimization to estimate an amplitude steering vector.
  • An Eigenvalue decomposition can be applied to the covariance for creating a monotonically decreasing function of the Lagrange multiplier.
  • Newton's method can be applied to solve for the Lagrange multiplier. Scaling ambiguity in the waveform can be eliminated by forcing a norm of the array steering vector to equal a number of transducers employed in capturing the thermoacoustic signals.
  • Waveform estimation of the pulse can include applying a weight vector to a pre-processed signal, wherein the weight vector is determined using the estimated array steering vector in a weight vector expression of a Capon beamformer.
  • the pre- processed signal can be a gain-scaled and time-shifted version of the received acoustic pulse.
  • uncertainty set allows the array steering vector to extend a range for phase measurement. By accommodating uncertainty in the array steering vector, amplitude distortions and phase distortions can be mitigated.
  • Another embodiment of the invention is an adaptive and robust detection method for use in thermoacoustic tomography.
  • the method can include estimating a bipolar acoustic pulse generated by a focal point from one or more thermoacoustic signals using robust Capon beamforming and searching for two peaks of the bipolar acoustic pulse within an interval around a calculated arrival time, and the interval is determined from an estimated variance of arrival time differences.
  • the method also can include calculating a response intensity at the focal point by calculating a peak-to-peak difference of the two peaks.
  • FIG. 1A is a schematic diagram of operative features of a thermoacoustic tomography (TAT) imaging system in accordance with an embodiment of the inventive arrangements;
  • TAT thermoacoustic tomography
  • FIG. 1 B is a plot of acoustic signals generated using a TAT imaging system in accordance with an embodiment of the inventive arrangements
  • FIG. 2 is a schematic diagram of a system for adaptive and robust techniques (ART) in TAT in accordance with an embodiment of the inventive arrangements
  • FIG. 3 is a schematic diagram of the processor of FIG. 2 in greater detail in accordance with an embodiment of the inventive arrangements
  • FIG. 4 is a method of adaptive and robust detection for high contrast and high resolution imaging in TAT in accordance with an embodiment of the inventive arrangements.
  • FIG. 5 further illustrates a method step of FIG. 4 for estimating an acoustic pulse in accordance with an embodiment of the inventive arrangements.
  • pressing can be defined as reducing or removing, either partially or completely.
  • processing can be defined as number of suitable processors, controllers, units, or the like that carry out a pre-programmed or programmed set of instructions.
  • the terms "program,” "software application,” and the like as used herein, are defined as a sequence of instructions designed for execution on a computer system.
  • a program, computer program, or software application may include a subroutine, a function, a procedure, an object method, an object implementation, an executable application, a source code, an object code, a shared library/dynamic load library and/or other sequence of instructions designed for execution on a computer system.
  • FIG. 1A a TAT imaging system 100 according to one embodiment of the invention is shown.
  • the TAT imaging system 100 can be used to create a tissue image from a reconstruction of thermoacoustic signals.
  • the TAT imaging system 100 can emit a stimulating electromagnetic pulse to a tissue 102.
  • the stimulating electromagnetic pulse can be, for example, a laser or a microwave emitting device that can be targeted at the focal point 104.
  • the biological tissue 102 under testing can absorb the stimulating electromagnetic pulse, which can cause a sudden heat change at the focal point 104. Accordingly, an acoustic pulse can be generated at the focal point 104 due to a thermoacoustic expansion effect in the tissue 102. [0028] Due to the thermoacoustic effect, the heating caused by the pulse results in expansion of the tissue, which in turn generates the acoustic signals. An image of the tissue absorption properties can be reconstructed from captured acoustic signals. The image reveals the physiological and pathological state of the tissue.
  • the TAT imaging system 100 can be used in many applications, including for example breast cancer detection.
  • the cancerous breast tissues typically have a two to five times higher microwave absorption rate than their surrounding normal breast tissues, which has been attributed to an increase in the amount of bound water and sodium within malignant cells.
  • An ultrasonic transducer array 106 can record the acoustic signals generated from the thermoacoustic effect.
  • the transducer array 106 may be a real aperture array or a synthetic aperture array formed by rotating a sensor around the tissue 102 and recording the acoustic signals at different locations.
  • the number of transducers in the array is M .
  • the number of transducer data acquisition locations can be M .
  • Each of the M transducers can be assumed to be omnidirectional.
  • the recorded acoustic signals can be sampled and digitized. Referring additionally to FIG. 1 B, a typical recorded acoustic signal 120 based on data measured from a breast specimen is shown.
  • the pulse 121 is a backscattered signal from the interface (e.g., a bowl holding the breast tissue).
  • the acoustic signal 120 also contains a reflection pulse 122 that is the acoustic pulse generated from the thermoacoustic effect in the tissue 102.
  • n is the discrete time index, starting from t 0 after the stimulating electromagnetic pulse 121.
  • the scalar s m ( ⁇ ) denotes the signal component, which corresponds to the acoustic pulse 122 generated at a focal point 104, and e m ⁇ n) is the residual term, which includes un-modeled noise and interference.
  • interference can be caused by other sources within the tissue such as multi-path propagation or refraction.
  • An image of thermoacoustic response intensity /(r) which is directly related to the absorption property of the tissue 102, can be reconstructed from the recorded data set ⁇ ,,,( ⁇ ) ⁇ .
  • the (2-D or 3-D) vector r denotes the focal point location coordinate 106.
  • the focal point 104 is scanned at location r to cover an entire cross-section of the tissue 102.
  • the transducers can acquire signals at different heights, wherein for each height, a 2-D cross-sectional image can be reconstructed and a 3-D image can be formed from the 2-D images.
  • the homogeneity of the tissue 102 can determine the distortion in the image.
  • the sound speed in human female breast varies widely from 1430 m/s to 1570 m/s around the commonly assumed speed of 1510 m/s.
  • the heterogeneous acoustic properties of biological tissues cause amplitude and phase distortions in the recorded acoustic signals, which can result in significant degradations in image quality. Accordingly, certain uncertainties can be allowed in ART to deal with amplitude and phase distortions caused by the background heterogeneity.
  • the discrete arrival time of the pulse (i.e., for the m th transducer) can be determined approximately as:
  • the dependence of the arrival time t m (r) on r can be omitted hereafter for notational simplicity.
  • At is the sampling interval, and the 3-D vector r m denotes the location of the mth transducer.
  • the sound speed v 0 can be chosen to be the average sound speed of the biological tissue under interrogation.
  • denotes the Euclidean norm of x
  • [_j ⁇ j indicates rounding to the greatest integer less than y .
  • the second term in (2) represents the time-of-f light between the focal point and the m th transducer.
  • a is the attenuation coefficient in Nepers/m.
  • TAT the major frequency components of the acoustic signals take a relatively narrow band, and are usually lower than those in UT.
  • the term a can be approximated as a frequency independent constant.
  • the acoustic signals can be preprocessed to align all the signals from the focal point r and compensate for the loss in amplitude due to propagation decay. For example, let yJri) denote the signal after preprocessing:
  • the signal of interest x(m) is the acoustic pulse 122, which has been shifted by a time factor t m and scaled by a gain term.
  • the time interval of interests for the signal y(t) can be defined to be from -N to N . Accordingly, N samples can be taken before and after the approximate arrival time given in Equation (2) for the focal point 106 at r .
  • N can be chosen large enough such that the interval from -N to N covers the expected pulse duration.
  • both the amplitude and the phase of the acoustic pulse are generally distorted.
  • the phase of the pulse signal can be considered the arrival time of the signal.
  • a major cause for these distortions is the acoustically heterogeneous background.
  • amplitude distortion is mainly due to the interferences caused by multi-path interference, which is inevitable in the heterogeneous medium. Refraction occurs due to acoustic speed mismatch across the tissue interface. Consequently, acoustic pulses arrive at the transducer via different routes and interfere with each other.
  • phase distortion is mainly caused by the non-uniform sound speed.
  • the sound speed can vary from 1430 m/s to 1570 m/s. Therefore the actual arrival time can fluctuate around the approximately calculated time given in Equation (2). Moreover, an inaccurate estimate of t 0 (t 0 is aligned with the focal point's signal arrival time) and the transducer calibration error may also contribute to the phase distortion. Amplitude and phase distortion can blur the image, raise the image background noise level, lower the values of the object of interest, and consequently decrease the image contrast. The effects of these distortions can be mitigated by allowing a 0 to belong to an uncertainty set centered at a and by considering the signal arriving within the interval from -N to N . [0035] Referring to FIG.
  • thermoacoustic tomography TAT
  • the system can include a receiver 202 for receiving one or more thermoacoustic signals emitted from a focal point in response to a heating of a tissue due to radiation absorption, wherein a thermoacoustic signal includes a pulse component and a noise component, a processor 204 for estimating a waveform of the pulse component by applying robust Capon beamforming to the multiple thermoacoustic signals for mitigating an amplitude and phase distortion of the waveform due to the noise component, and an image reconstruction unit 206 for evaluating a response intensity from the waveform for reconstructing a portion of an image of thermoacoustic response intensity corresponding to an absorption property of the tissue.
  • ART thermoacoustic tomography
  • the processor 204 can further include an analysis unit 210 for measuring an amplitude distortion from the thermoacoustic signals, wherein the amplitude distortion is associated with a refraction property of the tissue.
  • the processor 204 can further include a peak detector 214 for searching for a peak in the uncertainty range to estimate a phase distortion and comparing a location of the peak to an expected location, and a phase compensator 216 for providing a phase distortion correction to compensate the waveform for the phase distortion by shifting the waveform by the phase distortion.
  • the phase distortion can be associated with an acoustic speed variation due to said tissue.
  • a method 400 of adaptive and robust detection for use in thermoacoustic tomography is shown.
  • the method 400 is described herein with reference to FIGS. 1-3, but it should be noted that the method 400 can be practiced in any other suitable system or device.
  • the steps of the method 400 are not limited to the particular order in which they are presented in FIG. 4.
  • the method can also have a greater number of steps or a fewer number of steps than those shown in FIG. 4.
  • the ART algorithm illustratively comprises three steps: Step 410, robusst Capon beamforming (RCB) for robust waveform estimation; Step 430, peak-searching for phase aberration mitigation; and, Step 450, intensity calculation for forming the final images.
  • Step 410 robusst Capon beamforming (RCB) for robust waveform estimation
  • Step 430 peak-searching for phase aberration mitigation
  • Step 450 intensity calculation for forming the final images.
  • an acoustic pulse generated by a focal point from one or more thermoacoustic signals can be estimated using RCB.
  • the processor 204 can estimate the waveform of the acoustic pulse generated by the focal point at location r , based on the data model in Equation (5). It may appear that the presence of phase distortion has been neglected by using this data model in the first step. However, by allowing a 0 to be uncertain, some phase distortions can be tolerated which causes minimal performance degradation.
  • an array steering vector can be estimated using covariance fitting.
  • the processor 204 can employ covariance-fitting-based RCB to first estimate the steering vector a 0 .
  • Covariance fitting uses the estimated a 0 to obtain an optimal beamformer weight vector for pulse waveform estimation.
  • Equation (1) is a spherical uncertainty set, though an elliptical uncertainty set can be used if a tighter constraint is desirable. Notably, the uncertainity set accommodates an uncertainty range during phase measurement.
  • the array steering vector of Equation (6) maximizes a power of the pulse subject to the dual constraint optimization.
  • a Lagrange multiplier can be employed within a dual constraint optimization.
  • the solution to (1) is given by he following equation:
  • an Eigenvalue decomposition can be applied to the covariance for creating a monotonically decreasing function of the Lagrange multiplier.
  • Equation (4) the estimate So of the actual steering vector a 0 is determined by Equation (4).
  • Equation (1) there is a scaling ambiguity in Equation (1) by treating both the signal power ⁇ 2 and the steering vector a 0 as unknowns.
  • the ambiguity exists in the sense that ( ⁇ 2 ,a 0 ) and ( ⁇ 2 /c,c 1/2 a 0 ) (for any constant o 0) yields the same term ⁇ 2 a o ao .
  • the solution So is scaled to make its norm satisfy the following condition:
  • an optimal beamformer weight vector can be obtained for estimating a waveform of the pulse.
  • an optimal beamformer weight vector from the estimated array steering vector can be obtained for estimating a waveform of the pulse.
  • Equation (9) has a diagonal loading form, which allows the sample covariance matrix to be rank-deficient.
  • the beamformer output can be written as:
  • the weight vector has been applied to the pre-processed signal for estimating a pulse waveform.
  • the weight vector was determined using the array estimated steering vector in a weight vector expression of a Capon beamformer.
  • the estimated steering vector was generated by allowing an uncertainty set centered around the norminal steering vector.
  • the pre-processed signal of Equation (4) was a gain-scaled and time-shifted version of the acoustic pulse.
  • the estimated pulse waveform can be searched for a peak for mitigating a phase aberration. This is the second major step in ART.
  • the estimated pulse waveform was generated in steps 410-418.
  • the arrival time of the acoustic pulse generated by the focal point at location r can be accurately calculate using Equation (2).
  • this is rarely true in heterogeneous biological tissues as a result of the non-uniform sound speed through the heterogeneous tissue.
  • the heterogeneity is weak, such as in the breast tissue, amplitude distortion caused by multi-path is not severe. Accordingly, the original peak can be assumed to remain as a peak in the waveform estimate for the acoustic pulse generated in step 410.
  • the peak detector 214 searches for a peak in an uncertainty range to estimate a phase distortion.
  • the peak detector 214 can search for the peak within an interval around an estimated arrival time, wherein the interval is determined from an estimated variance of arrival time differences.
  • the processor 204 calculates an arrival time of the pulse component based on the peak; aligns one or more thermoacoustic signals based on the arrival time, and compensates for a loss in amplitude due to a propagation decay associated with the tissue.
  • the bipolar acoustic pulse has one positive peak and a negative peak.
  • the positive and negative peak values can be determined as follows:
  • the searching range [- ⁇ , ⁇ ] ⁇ [-JV 9 N] is around the calculated arrival time given by Equation (2).
  • ⁇ is a user parameter. Since the peak searching is independent of the particular waveform estimation methods, we use s(ri) to denote the waveform estimated by either DAS or ART.
  • the search range is determined by the difference between the true arrival time F n , and the calculated arrival time t m based on Equation
  • r' is a point within the line connecting the focal point at location r and the m th transducer at location r OT
  • v(r') is the local sound speed.
  • the higher order terms of [v(r')-v o ]/v o have been ignored. It is reasonable to assume that v(r') is Gaussian distributed with mean v 0 and variance ⁇ 2 . Consequently the arrival time difference is also Gaussian distributed with zero-mean and variance ⁇ ] ⁇ ⁇ v 2 /v 0 2 .
  • a search range can be empirically based on an estimated variance of the arrival time difference ⁇ s ⁇
  • the search interval can be determined from an estimated variance of arrival time differences, wherein the variance is generated is step 410 by perturbing an array steering vector for allowing an uncertainty in phase measurement.
  • a response intensity can be calculated from the identified peak for forming one portion of an image.
  • a response intensity can be obtained based on the estimated waveform.
  • Two different types of response intensity measurement approaches are amplitude based and energy based, respectively.
  • the waveform peak values obtained in Step 430 of ART can be used for both approaches.
  • Conventional DAS uses the amplitude based measure for TAT imaging, with the corresponding response intensity given by S(O) , or equivalently:
  • the energy-based measure calculates the response intensity as follows:
  • E1 means "Energy-type 1."
  • the entire pulse energy can also be used as an intensity measure, such as in the mono-static and multi-static microwave imaging for breast cancer detection, and the intensity is given by:
  • Peak-searching maximizes the output signal-to-noise ratio.
  • An intuitive explanation is that, given the fact that the acoustic pulse is bipolar, if one assumes that the residual term e(t) is stationary, or its power is uniform over time, then the signal-to- noise ratio is maximized at the (positive or negative) peak of the acoustic pulse.
  • a conventional DAS fixes the samples to be summed up at the calculated arrival time. Due to phase distortions, the waveform at the calculated time may be far from the peak value.
  • the peak-to-peak difference can be employed as the response intensity for the focal point at location r :
  • Peak-to-peak difference has higher imaging contrast than peak value measure: the peak-to-peak difference of the bipolar pulse is approximately twice the absolute peak value; that is, the output signal power of the former is four times of the latter; yet the noise power of the former is only twice of the latter.
  • SNR Signal-to-Noise Ratio
  • the method of adaptive and robust detection for use in thermoacoustic tomography can include estimating a bipolar acoustic pulse generated by a focal point from one or more thermoacoustic signals using robust Capon beamforming, searching for two peaks of the bipolar acoustic pulse within an interval around a calculated arrival time (the interval being determined from an estimated variance of arrival time differences, and the variance being generated by perturbing an array steering vector for allowing an uncertainty in phase measurement) and calculating a response intensity at the focal point by calculating a peak-to-peak difference of the two peaks.
  • the image reconstruction unit 206 can enhance a contrast of the image by using the peak-to-peak difference for providing a response intensity of the focal point, wherein the waveform is bipolar having a positive peak corresponding to a compression pulse and a negative peak corresponding to a refraction pulse.
  • the present embodiments of the invention can be realized in hardware, software or a combination of hardware and software. Any kind of computer system or other apparatus adapted for carrying out the methods described herein are suitable.
  • a typical combination of hardware and software can be a mobile communications device with a computer program that, when being loaded and executed, can control the mobile communications device such that it carries out the methods described herein.
  • Portions of the present method and system may also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein and which when loaded in a computer system, is able to carry out these methods.

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Abstract

La présente invention concerne un procédé et un système de détection adaptative et robuste pour une utilisation dans une tomographie thermo-acoustique. Le procédé comprend l'estimation (410) d'une impulsion acoustique bipolaire générée par un point focal à partir de multiples signaux thermo-acoustiques à l'aide de la formation de faisceau Robust Capon, la recherche (430) de deux crêtes de l'impulsion acoustique bipolaire dans un intervalle autour d'un temps d'arrivée calculé, l'intervalle étant déterminé à partir d'une variation estimée des différences des temps d'arrivée ; et le calcul (450) d'une intensité de réponse au point focal par le calcul d'une différence entre les deux crêtes.
PCT/US2007/065680 2006-03-31 2007-03-30 Procede et systeme pour une detection adaptative et robuste WO2007115200A2 (fr)

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Cited By (4)

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CN102439418A (zh) * 2009-06-12 2012-05-02 奥林巴斯株式会社 被检体信息分析装置以及被检体信息分析方法
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CN102439418A (zh) * 2009-06-12 2012-05-02 奥林巴斯株式会社 被检体信息分析装置以及被检体信息分析方法
JP2012105963A (ja) * 2010-10-27 2012-06-07 Fujifilm Corp 光音響撮像装置およびその作動方法
CN111265245A (zh) * 2020-01-20 2020-06-12 西安交通大学 基于双约束鲁棒Capon波束合成和多重变迹互相关的被动空化成像方法及系统
CN111265245B (zh) * 2020-01-20 2021-02-09 西安交通大学 基于双约束鲁棒Capon波束合成和多重变迹互相关的被动空化成像方法及系统

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