CN111289470A - OCT measurement imaging method based on computational optics - Google Patents
OCT measurement imaging method based on computational optics Download PDFInfo
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- 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
- G01N21/41—Refractivity; Phase-affecting properties, e.g. optical path length
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- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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Abstract
An OCT measurement imaging method based on computational optics comprises the steps of firstly carrying out raster scanning interference imaging on a sample through a Fourier domain OCT system, and then carrying out photoelectric conversion and multipoint sampling on spectral domain interference fringes obtained by imaging by using a photoelectric conversion device; and after the discrete spectrum signal is obtained, performing constraint optimization calculation, and finally realizing super-resolution image reconstruction exceeding the physical bandwidth. The method breaks through the limitation of the axial resolution obtained by the traditional discrete Fourier transform, and the resolution capability of the super-resolution reconstruction signal and the clear image exceeds the full width at half maximum of a coherent system.
Description
Technical Field
The invention relates to a technology in the optical field, in particular to an Optical Coherence Tomography (OCT) measurement imaging method based on numerical calculation.
Background
The OCT utilizes the basic principle of a weak coherent light interferometer to detect back scattering signals of incident weak coherent light on different depth levels of biological tissues, and then two-dimensional or three-dimensional structural images of the biological tissues are obtained through scanning. The method has the good characteristics of no damage, high resolution, high imaging speed, non-invasion (noninvaive) and the like. The reconstruction methods in the existing OCT theory are all based on Inverse Discrete Fourier Transform (IDFT), and it is generally considered that the obtained axial resolution is approximately equal to the coherence length of the light source and inversely proportional to the bandwidth of the emission spectrum of the OCT system, and for technical reasons, the resolution can reach about 1 μm at most. In the last decade, improving OCT resolution has primarily been through physically increasing the bandwidth of the system. However, the resolution is further improved with some difficulty by using this method.
Disclosure of Invention
Aiming at the problems and defects in the conventional IDFT reconstruction method, the invention provides the OCT measurement imaging method based on computational optics, which breaks through the limitation of the traditional discrete Fourier transform method on the axial resolution, and the resolution of the obtained reconstruction signal and image is far smaller than the coherence length of the system.
The invention is realized by the following technical scheme:
the invention relates to an OCT measurement imaging method based on computational optics, firstly, a Fourier domain OCT system is used for carrying out raster scanning (raster scan) interference imaging on a sample, and then a photoelectric conversion device is used for carrying out photoelectric conversion and multipoint sampling on spectral domain interference fringes obtained by imaging; and after the discrete spectrum signal is obtained, carrying out constraint optimization calculation on the discrete spectrum signal, and finally realizing super-resolution image reconstruction exceeding the physical bandwidth of the discrete spectrum signal.
The photoelectric conversion device is a photoelectric detector or a photoelectric coupling camera and the like, and performs photoelectric conversion on the spectral domain interference fringes obtained by imaging to obtain a coherent spectrum of a scanned image.
The multipoint sampling refers to: the coherent spectrum is oversampled in a digital-to-analog converter, namely, a speed exceeding a nyquist sampling frequency is used for acquiring as many sampling points N as possible, and a discrete spectrum signal is obtained.
The constraint optimization calculation refers to: and substituting the discrete spectrum signal into an inverse problem mathematical model to perform optimization iterative solution, and realizing super-resolution image reconstruction exceeding the physical bandwidth.
The inverse problem mathematical model is as follows:wherein:which is representative of the original signal, is,represents the objective function to be optimized and,representing any constraint such as L1 norm TV, etc.
The Fourier domain OCT system divides a low-coherence optical signal emitted by a light source into two beams through a light beam splitter (coupler), the two beams are respectively reflected by a reference reflector and a sample, reflected light of two arms is coupled into one beam through the coupler again and output, and a high-resolution image is reconstructed through photoelectric detection, digital-to-analog conversion and constraint optimization calculation.
Technical effects
The invention makes up the defects of the prior art as a whole, and enables the axial resolution not to be limited by the full width at half maximum of the system. Compared with the prior art, the invention can achieve higher axial resolution capability than that obtained by IDFT under various conditions (including low SNR condition) and has good noise resistance. The method is practically applied to optical slice images: when the onion sample slice is used for image reconstruction, as shown in fig. 2, the method provided by the invention can achieve a clearer image effect and stronger noise resistance compared with the traditional imaging method, the double-layer membrane structure of the onion can be clearly distinguished in image reconstruction of the cornea of the monkey eye, as shown in fig. 3, better contrast can be obtained by using the method provided by the invention, and the arrow in the figure shows a clear eyeground elastic membrane structure.
Drawings
Fig. 1 is a schematic diagram of an embodiment signal, and fig. 1 is a schematic diagram of an embodiment signal, wherein (a) to (d) are images reconstructed by different methods when the distance is 20 micrometers, 15 micrometers is 10 micrometers, and 5 micrometers are respectively.
FIG. 2 is a schematic diagram of image reconstruction of onion specimen slices according to the embodiment, wherein (a) - (d) respectively adopt: full bandwidth, 1/2 bandwidth, 1/4 bandwidth and 1/8 bandwidth, the left two columns are the image restored by IDFT and its enlarged image, and the right image is the image restored by the method and its enlarged image.
FIG. 3 is a schematic diagram of image reconstruction of a cornea sample slice of a monkey eye, in which ((a), (c) are images restored by IDFT and their enlarged images, and (b) and (d) are images restored by the method and their enlarged images, respectively.
Detailed Description
Simulation example: two reflecting surfaces at different distances are taken as hypothetical samples, a frequency spectrum imaged and sampled by a Fourier domain OCT system is taken as a signal, and the following three methods are used for image reconstruction and comparison: (1) IDFT (2) IDFT followed by Lucy-Richardson deconvolution (3) the constraint optimization method proposed by the present invention. Among them, for the constrained optimization method, two different constraints are used (1) and no constraint (2) use sparse constraint, i.e., L2 and L1 methods described later. The parameters used in the simulation were as follows: the light source emission spectrum is supposed to meet the requirement of Gaussian waveform, central wavelength of 1310nm, full width at half maximum of 40nm, spectrum measurement range of 1260-1360 nm and 1024 spectrum sampling points. The effective domain of the simulated object is 0-1 mm, the grid interval when discretizing the object is 100nm (or any smaller length), and the grid interval of the reconstructed image is 2 μm (since the interval is much smaller than the grid interval reconstructed in the IDFT method, it is called as a fine grid). The experimental data obtained are shown in FIG. 1. In this example, the axial resolution of the image reconstructed using the IDFT method commonly used in OCT is about 19 μm. The best resolution (fine grid plus L1 norm) achieved by the method of the present invention is at least 5 μm or more, and is better than the method using deconvolution.
Example 1
In the embodiment, a sample slice image of an onion is reconstructed, a fourier domain OCT system is used for performing raster scanning (raster scan) interference imaging on a sample, then a photoelectric conversion device is used for performing photoelectric conversion and oversampling on spectral domain interference fringes obtained by imaging, after a discrete spectrum signal is obtained, constraint optimization calculation is performed, and super-resolution image reconstruction is finally achieved.
The fourier domain OCT system is a commercial optical coherence tomography (SD-OCT) system (GAN620C1, Thorlabs, usa), the spectrum center frequency is 892.8nm, and the spectrometer measurement range is: 791.6-994.0 nm, 2048 pixels. Different bandwidths are adopted by truncation, and as shown in fig. 2(a) - (d): the full bandwidth, 1/2 bandwidth, 1/4 bandwidth and 1/8 bandwidth, and experimental results show that the image obtained by the method has higher resolution, and the onion double-layer film structure can be seen, which is superior to the traditional IDFT reconstruction method.
The constraint used in this example is a sparseness condition (L1) where the grid spacing of the reconstructed image is 1 μm.
Example 2
In this example, a sample slice image of a cornea of an eye of a living monkey is reconstructed, a self-made super-resolution optical coherence tomography (SD-OCT) system is used as an imaging system, a light source adopts Cblmd-t-850-HP-I of Superlum in Ireland, the central wavelength is 850nm, the actual measurement of the full width at half maximum (FWHM) is 125nm, the measured actual coherence length is 2.8 μm, and the imaging range of a spectrometer is about 2.6 mm. The results of the images are shown in fig. 3, and the method of the present invention can obtain better contrast than the super-resolution imaging system, and the arrow in fig. 3(d) shows the clear structure of the elastic membrane of the fundus oculi of the monkey.
Compared with the prior art, the method adopting the fine grid and the L1 norm can improve the axial resolution by at least two times, is far lower than the coherence length of a system, and can achieve higher resolution compared with the traditional IDFT-based reconstruction method.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (6)
1. An OCT measurement imaging method based on computational optics is characterized in that a Fourier domain OCT system is used for carrying out raster scanning interference imaging on a sample, and then a photoelectric conversion device is used for carrying out photoelectric conversion and multipoint sampling on spectral domain interference fringes obtained by imaging; and after the discrete spectrum signal is obtained, performing constraint optimization calculation, and finally realizing super-resolution image reconstruction exceeding the physical bandwidth.
2. The OCT measurement imaging method according to claim 1, wherein the photoelectric conversion device is a photoelectric detector or a photoelectric coupled camera, and performs photoelectric conversion on the spectral domain interference fringes obtained by imaging to obtain a coherent spectrum of the scanned image.
3. The OCT measurement imaging method of claim 1, wherein the multi-point sampling is: the coherent spectrum is oversampled in a digital-to-analog converter, namely sampling at a sampling frequency exceeding the nyquist sampling frequency so as to obtain as many sampling points N as possible, and a discrete spectrum signal with low resolution is obtained.
4. The OCT measurement imaging method of claim 1, wherein the constrained optimization calculation comprises: and substituting the discrete spectrum signal into an inverse problem mathematical model to perform optimization iterative solution, and realizing super-resolution image reconstruction exceeding the physical bandwidth.
6. The OCT measurement imaging method of claim 1, wherein the Fourier domain OCT system divides a low coherence light signal emitted by a light source into two beams through a light beam splitter (coupler), the two beams are respectively reflected by a reference reflector and a sample, reflected light of the two arms is coupled into one beam through the coupler again and output, and a high resolution image is reconstructed through photoelectric detection, digital-to-analog conversion and constraint optimization calculation.
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Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114022583A (en) * | 2021-10-12 | 2022-02-08 | 佛山市灵觉科技有限公司 | OCT image reconstruction method based on non-uniform discrete Fourier transform |
CN114372915A (en) * | 2021-12-07 | 2022-04-19 | 图湃(北京)医疗科技有限公司 | Method for realizing OCT axial super resolution |
CN116050230A (en) * | 2022-10-25 | 2023-05-02 | 上海交通大学 | Full-wavelength signal simulation method of FD-OCT (fiber-optic coherence tomography) based on Monte Carlo |
CN114022583B (en) * | 2021-10-12 | 2024-05-14 | 佛山市灵觉科技有限公司 | OCT image reconstruction method based on non-uniform discrete Fourier transform |
Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1128131A (en) * | 1994-10-05 | 1996-08-07 | 卡尔蔡斯公司 | Optical coherence tomography corneal mapping apparatus |
CN1623085A (en) * | 2002-01-24 | 2005-06-01 | 通用医疗公司 | 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 |
CN1804657A (en) * | 2006-01-23 | 2006-07-19 | 武汉大学 | Small target super resolution reconstruction method for remote sensing image |
CN201019719Y (en) * | 2007-03-29 | 2008-02-13 | 浙江大学 | Spectrum region OCT endoscopic image pick-up device used for in situ optical biopsy |
CN101427911A (en) * | 2008-12-22 | 2009-05-13 | 浙江大学 | Method and system for detecting ultra-broadband optical spectrum of ultrahigh-resolution spectrum field OCT |
CN104574338A (en) * | 2015-01-26 | 2015-04-29 | 西安交通大学 | Remote sensing image super-resolution reconstruction method based on multi-angle linear array CCD sensors |
CN105023282A (en) * | 2014-04-30 | 2015-11-04 | 华中科技大学 | Sparse projection ultrasonic CT image reconstruction method based on CS |
US20160178354A1 (en) * | 2010-10-15 | 2016-06-23 | Bioaxial Sas | Method and device for superresolution optical measurement using singular optics |
WO2016193393A1 (en) * | 2015-06-05 | 2016-12-08 | Université Du Luxembourg | Real-time temporal filtering and super-resolution of depth image sequences |
CN108961261A (en) * | 2018-03-14 | 2018-12-07 | 中南大学 | A kind of optic disk region OCT image Hierarchical Segmentation method based on spatial continuity constraint |
CN109489544A (en) * | 2018-10-24 | 2019-03-19 | 江苏度微光学科技有限公司 | Super-resolution optical coherent chromatography method and system based on optical microstructures |
CN110335327A (en) * | 2019-07-10 | 2019-10-15 | 东北大学 | A kind of medical image method for reconstructing directly solving inverse problem |
CN110715730A (en) * | 2018-07-11 | 2020-01-21 | 唯亚威通讯技术有限公司 | Focus linear model correction and linear model correction for multivariate calibration model maintenance |
-
2020
- 2020-02-06 CN CN202010081697.5A patent/CN111289470B/en active Active
Patent Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1128131A (en) * | 1994-10-05 | 1996-08-07 | 卡尔蔡斯公司 | Optical coherence tomography corneal mapping apparatus |
CN1623085A (en) * | 2002-01-24 | 2005-06-01 | 通用医疗公司 | 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 |
CN1804657A (en) * | 2006-01-23 | 2006-07-19 | 武汉大学 | Small target super resolution reconstruction method for remote sensing image |
CN201019719Y (en) * | 2007-03-29 | 2008-02-13 | 浙江大学 | Spectrum region OCT endoscopic image pick-up device used for in situ optical biopsy |
CN101427911A (en) * | 2008-12-22 | 2009-05-13 | 浙江大学 | Method and system for detecting ultra-broadband optical spectrum of ultrahigh-resolution spectrum field OCT |
US20160178354A1 (en) * | 2010-10-15 | 2016-06-23 | Bioaxial Sas | Method and device for superresolution optical measurement using singular optics |
CN105023282A (en) * | 2014-04-30 | 2015-11-04 | 华中科技大学 | Sparse projection ultrasonic CT image reconstruction method based on CS |
CN104574338A (en) * | 2015-01-26 | 2015-04-29 | 西安交通大学 | Remote sensing image super-resolution reconstruction method based on multi-angle linear array CCD sensors |
WO2016193393A1 (en) * | 2015-06-05 | 2016-12-08 | Université Du Luxembourg | Real-time temporal filtering and super-resolution of depth image sequences |
CN108961261A (en) * | 2018-03-14 | 2018-12-07 | 中南大学 | A kind of optic disk region OCT image Hierarchical Segmentation method based on spatial continuity constraint |
CN110715730A (en) * | 2018-07-11 | 2020-01-21 | 唯亚威通讯技术有限公司 | Focus linear model correction and linear model correction for multivariate calibration model maintenance |
CN109489544A (en) * | 2018-10-24 | 2019-03-19 | 江苏度微光学科技有限公司 | Super-resolution optical coherent chromatography method and system based on optical microstructures |
CN110335327A (en) * | 2019-07-10 | 2019-10-15 | 东北大学 | A kind of medical image method for reconstructing directly solving inverse problem |
Non-Patent Citations (2)
Title |
---|
JUN KE等: "Image reconstruction from nonuniformly spaced samples in spectral-domain optical coherence tomography", 《BIOMEDICAL OPTICS EXPRESS》 * |
QIFAN WANG 等: "Super-Resolution in Optical Coherence Tomography", 《2018 40TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)》 * |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114022583A (en) * | 2021-10-12 | 2022-02-08 | 佛山市灵觉科技有限公司 | OCT image reconstruction method based on non-uniform discrete Fourier transform |
CN114022583B (en) * | 2021-10-12 | 2024-05-14 | 佛山市灵觉科技有限公司 | OCT image reconstruction method based on non-uniform discrete Fourier transform |
CN114372915A (en) * | 2021-12-07 | 2022-04-19 | 图湃(北京)医疗科技有限公司 | Method for realizing OCT axial super resolution |
CN114372915B (en) * | 2021-12-07 | 2023-05-23 | 图湃(北京)医疗科技有限公司 | Method for realizing OCT axial super-resolution |
CN116050230A (en) * | 2022-10-25 | 2023-05-02 | 上海交通大学 | Full-wavelength signal simulation method of FD-OCT (fiber-optic coherence tomography) based on Monte Carlo |
CN116050230B (en) * | 2022-10-25 | 2023-08-22 | 上海交通大学 | Full-wavelength signal simulation method of FD-OCT (fiber-optic coherence tomography) based on Monte Carlo |
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