CN111627085A - Wavefront sub-field curvature sensing method and device and self-adaptive OCT system - Google Patents
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Abstract
The application discloses a wavefront sub-field curvature sensing method and device and a self-adaptive OCT system, comprising the following steps: the split spherical mirror receives and reflects parallel light returned by a sample arm in the self-adaptive OCT system; the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times respectively to obtain a light intensity distribution pattern; the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes an intrinsic Zernike polynomial coefficient as output to train a neural network; the wave front information fitting module obtains the whole wave front information through nonlinear fitting of a neural network according to the left-right symmetry of the aberration of the human eye; the aberration correction module takes the wavefront information as feedback and corrects the aberration by adjusting the deformable mirror so as to acquire diffraction limit imaging. The method combines the wavefront sensing technology and the machine learning algorithm, can improve the imaging capability of the self-adaptive OCT, and reduces the influence of the error of the optical path and the eyes.
Description
Technical Field
The invention relates to the technical field of optical imaging, in particular to a wavefront sub-field curvature sensing method and device and a self-adaptive OCT system.
Background
Optical Coherence Tomography (OCT) is a novel imaging technique based on Optical Coherence properties, which analyzes and detects interference signals of backscattered or reflected light and reference light of a biological tissue sample, and performs Tomography on the internal structure of the biological tissue sample to obtain tissue characteristics of an Optical tomographic image, so as to determine an object to be identified for diagnosis. Compared with the conventional imaging means, the OCT technology has unique advantages, the imaging effect of the OCT technology is close to pathology, and the OCT technology has the advantages of non-invasive and non-radiative properties, real-time observation of living bodies, high resolution (16 micrometers), in-tissue depth imaging, 3D image data and the like. OCT technology has become an important tool for detecting retinal diseases.
In order to improve the transverse resolution of optical retina imaging, Adaptive Optics (AO) and OCT are generally combined, but in the existing adaptive OCT (AO-OCT) technology, the wavefront sensing is greatly influenced by the uniformity of pupil illumination, and has the defects of easy pupil inclination, large dispersion influence, insufficient range, low resolving robustness and the like.
Therefore, how to improve the imaging capability of the adaptive OCT is a technical problem that needs to be solved urgently by those skilled in the art.
Disclosure of Invention
In view of this, the present invention provides a wavefront subfield curvature sensing method and apparatus, and a self-adaptive OCT system, which can improve the imaging capability of the self-adaptive OCT, reduce the influence of the error between the optical path and the eye itself, and improve the robustness. The specific scheme is as follows:
a wavefront subfield curvature sensing method for an adaptive OCT system, comprising:
the split spherical mirror receives and reflects parallel light returned by a sample arm in the self-adaptive OCT system;
the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times respectively to obtain a light intensity distribution pattern;
the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes an intrinsic Zernike polynomial coefficient as output to train a neural network;
the wave front information fitting module obtains distorted whole wave front information through the trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration;
and the aberration correction module takes the obtained wavefront information as feedback and corrects aberration by adjusting a deformable mirror in the adaptive OCT system so as to acquire diffraction limit imaging.
Preferably, in the method for sensing curvature of a wavefront subfield provided by an embodiment of the present invention, the acquiring far-field images of sample arms having the same defocus amount on both sides of a focal plane respectively includes:
and respectively acquiring far-field images of the sample arm with the same defocusing amount on two sides of a focal plane by a single exposure mode.
Preferably, in the above method for sensing curvature of a wavefront subfield provided by an embodiment of the present invention, the neural network uses a wavelet function as a hidden layer activation function.
Preferably, in the method for sensing curvature of a wavefront subfield provided by an embodiment of the present invention, the method further includes:
the spectroscope or the reflector receives the parallel light reflected by the split spherical mirror and reflects the parallel light to the image acquisition module.
Preferably, in the method for sensing curvature of a wavefront split-field provided by the embodiment of the present invention, the image capturing module is a CCD camera.
Preferably, in the method for sensing curvature of a wavefront subfield provided by an embodiment of the present invention, the image capturing module moves through a guide rail installed below the image capturing module.
The embodiment of the invention also provides a wave front sub-field curvature sensing device, which comprises:
the split spherical mirror is used for receiving and reflecting parallel light returned by a sample arm in the self-adaptive OCT system;
the image acquisition module is used for receiving the reflected parallel light and respectively acquiring sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times to obtain a light intensity distribution pattern;
the network training module is used for training a neural network by taking subtraction of two obtained light intensity distribution patterns as input and taking an intrinsic Zernike polynomial coefficient as output;
the wave front information fitting module is used for obtaining distorted whole wave front information through the trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration;
and the aberration correction module is used for taking the obtained wavefront information as feedback and correcting aberration by adjusting a deformable mirror in the adaptive OCT system so as to acquire diffraction limit imaging.
Preferably, in the above wavefront subfield curvature sensing device provided in the embodiment of the present invention, further includes:
the spectroscope or the reflector is used for receiving the parallel light reflected by the split spherical mirror and reflecting the parallel light to the image acquisition module.
Preferably, in the wavefront curvature sensing device according to the embodiment of the present invention, the image capturing module is a CCD camera; the CCD camera moves through a guide rail installed below the CCD camera.
The embodiment of the present invention further provides a self-adaptive OCT system, including: the low-coherence light source, the optical fiber coupler, the reference arm, the sample arm and the spectrometer are connected with each other through optical fibers; the sample arm comprises a first spectroscope, a deformable mirror and a scanning mechanism, and further comprises the wavefront subfield curvature sensing device provided by the embodiment of the invention; wherein,
the fiber coupler is used for dividing the weak coherent light into a first light beam and a second light beam, wherein the first light beam enters the sample arm, and the second light beam enters the reference arm;
the reference arm is used for returning the first light beam to the optical fiber coupler after being reflected;
the sample arm is used for focusing the second light beam to the deformable mirror through the first beam splitter, reflecting the second light beam to the scanning mechanism through the deformable mirror, scanning the fundus to be detected through the scanning mechanism, reflecting the scanned light beam backwards, returning the light beam along the original path, dividing the light beam into two parts after reaching the first beam splitter, reflecting one part of the light beam to the wavefront field curvature sensing device to obtain distorted whole wavefront information, using the obtained wavefront information as feedback, correcting aberration by adjusting the deformable mirror in the adaptive OCT system, and enabling the other part of the light beam to enter the optical fiber coupler;
and the spectrometer is used for receiving the light reflected by the reference arm and the sample arm and collecting an interference pattern.
According to the technical scheme, the wavefront subfield curvature sensing method and device and the self-adaptive OCT system provided by the invention comprise the following steps: the split spherical mirror receives and reflects parallel light returned by a sample arm in the self-adaptive OCT system; the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times respectively to obtain a light intensity distribution pattern; the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes an intrinsic Zernike polynomial coefficient as output to train a neural network; the wave front information fitting module obtains distorted whole wave front information through trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration; the aberration correction module takes the obtained wavefront information as feedback, and corrects aberration by adjusting a deformable mirror in the adaptive OCT system to acquire diffraction limit imaging.
The invention combines the wave-front sensing technology and the machine learning algorithm, estimates the wave-front curvature change through the light intensity distribution of the split spherical mirror before and after focus images, and calculates the wave-front information through the neural network nonlinear fitting, corrects the aberration by the wave-front information, promotes the rapid aberration measurement and the non-aberration correction in the self-adaptive OCT imaging process, reduces the tissue interference, realizes the diffraction limit imaging, can rapidly improve the imaging capability of the self-adaptive OCT, reduces the influence of the error of the light path and the eyes, promotes the robustness and has good application prospect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or technical solutions in related arts, the drawings used in the description of the embodiments or related arts will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flow chart of a wavefront subfield curvature sensing method according to an embodiment of the present invention;
fig. 2 is a schematic view of light transmission between a split spherical mirror and a CCD camera according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of curvature sensing provided by an embodiment of the present invention;
FIG. 4 is a schematic diagram of data resolution provided by an embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a wavefront subfield curvature sensing device according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an adaptive OCT system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a wavefront subfield curvature sensing method, as shown in fig. 1, comprising the following steps:
s101, receiving and reflecting parallel light returned by a sample arm in the self-adaptive OCT system by a split spherical mirror;
it should be noted that the split spherical mirror is a standard spherical mirror divided into two halves, that is, the split spherical mirror is divided into two parts, fig. 2 shows the structure of the split spherical mirror 11, which can be respectively imaged before and after focusing;
s102, the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane (namely before and after the focal plane) for multiple times respectively to obtain a light intensity distribution pattern;
in particular implementation, as shown in fig. 2, the image capture module 12 may be a CCD camera. In practical application, the image acquisition module 12 can move through a guide rail installed below the image acquisition module, that is, after parallel light reflected by the split spherical mirror enters the CCD camera, the two images can be guaranteed to be in front of and behind one another through the movement of the guide rail;
s103, the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes intrinsic Zernike polynomial coefficients as output to train a neural network;
it should be noted that when the fitting order is increased, the lack of order is serious, or the same result can be achieved through fewer orders, previously, because the linear correlation is too strong, in order to fit some frequency components, a very high order needs to be increased, the too high order may cause matrix morbidity, and the current highest fitting can only process the result by using 16-18 orders or using nonlinear optimization. The invention uses 'eigenmode' to solve the problem, namely, Zernike polynomials on a semicircular aperture are orthogonalized, and the base adopts the eigenmode and expresses aberration by using an intrinsic Zernike polynomial coefficient;
s104, the wave front information fitting module obtains distorted whole wave front information through trained neural network nonlinear fitting according to the bilateral symmetry of human eye aberration;
and S105, the aberration correction module takes the obtained wavefront information as feedback and corrects the aberration by adjusting a deformable mirror in the self-adaptive OCT system so as to acquire diffraction limit imaging.
In the wavefront field curvature sensing method provided by the embodiment of the invention, the wavefront sensing technology and the machine learning algorithm are combined, the wavefront curvature change is estimated through the light intensity distribution of the split spherical mirror before and after the focus, and the wavefront information is calculated through the neural network nonlinear fitting, so that the aberration is corrected by the wavefront information, the rapid aberration measurement and the aberration-free correction in the self-adaptive OCT imaging process are improved, the tissue interference is reduced, the diffraction limit imaging is realized, the imaging capability of the self-adaptive OCT can be rapidly improved, the influence of the error of an optical path and an eye is reduced, the robustness is improved, and the application prospect is good.
The curvature sensing principle of the wavefront subfield curvature sensing method provided by the embodiment of the present invention is described in detail below by taking fig. 3 as an example:
the curvature of the wavefront at the pupil is changed locally, and the light intensity distribution of the corresponding in-focus image and the out-of-focus image is changed correspondingly. According to the transmission equation of the near-field electromagnetic wave, the wavefront information can be solved, as shown in formula (1):
wherein,
in order to be of a strength,
for phase, ▽ is a gradient operator, the result is a slope, ▽2The laplacian operator, the result is the curvature.
Are coordinates within the pupil, and are,
in the above equation, γ is defined as 1 as a pupil coordinate in the image plane. It can be seen that the results are related to both slope curvature.
For an adaptive optical system, generally, the defocus amount is only a few focal depths, the defocused star point image is very close to the pupil shape, and after subtraction, it can be considered that:
wherein R is the radius of the light spot.
Thus, formula (1) can be approximated by formula (2):
wherein, P1And P2Two symmetrical planes with defocus amount of l at both sides of the focal plane, and Δ z is P1P2The distance between the conjugate position and the entrance pupil is shown in formula (3):
Δz＝f(f-l)/l (3)
is provided with
Bringing formula (2) can yield formula (4).
The Poisson equation can be solved for the formula (4), and the deformable mirror in the self-adaptive OCT system can automatically converge towards the surface shape meeting the Poisson equation; here, the wavefront of the full aperture is estimated using the half aperture.
Through fast Fourier transform
Therefore, the method can obtain:
with P1For example, the conversion relationship between the focal plane and the pupil plane is shown in formula (6), and is based on the conversion relationship at P1The light intensity distribution obtained by the position is
At P2The light intensity distribution obtained by the position is
In specific implementation, in the method for sensing curvature of a wavefront subfield provided in an embodiment of the present invention, the acquiring far-field images of sample arms having the same defocus amount on both sides of a focal plane respectively specifically includes: and respectively acquiring far-field images of the sample arm with the same defocusing amount on two sides of a focal plane by a single-shot (single-shot) mode. The method can realize the acquisition of the pre-focus image and the post-focus image without moving parts, realizes simultaneous measurement, utilizes the characteristic that the curvature sensor is slightly influenced by the aperture, is based on the sub-field detection of the extended target of the eyeground, and finally obtains complete wavefront distortion information through a synthesis algorithm.
In specific implementation, in the above method for sensing curvature of a wavefront subfield provided by the embodiment of the present invention, the neural network may use a wavelet function as a hidden layer activation function. The wavelet neural network combines the characteristics of wavelet transformation multi-scale representation, and simultaneously retains the characteristics of good generalization capability and strong nonlinear mapping capability of the neural network.
It should be understood that machine learning is a branch field of artificial intelligence, and aims to autonomously learn in a large amount of empirical data, induce and discover the relationship between variables in the system, summarize and use an algorithm to continuously improve a weight value, and finally predict unknown data. When the existing rules and formulas can not describe common aberration and system errors, the machine learning model is established to process a large amount of data, so that great flexibility and adaptability are shown. As shown in FIG. 4, the present invention first rotates two light intensity distribution patterns, then aligns them, and then subtracts them, and trains the neural network with the two subtracted light intensity distribution patterns as input and the intrinsic Zernike polynomial coefficient as output.
In addition, it should be noted that the invention constructs a system error (gravity, temperature, airflow, vibration, actuator error, optical element surface shape error, polarization error, light intensity flicker) model from end to end based on a deep learning algorithm, thereby realizing calibration of the system and reducing the pressure of hardware realization.
In specific implementation, in the method for sensing curvature of a wavefront subfield provided by the embodiment of the present invention, the method may further include: the spectroscope or the reflector receives the parallel light reflected by the split spherical mirror and reflects the parallel light to the image acquisition module.
Based on the same inventive concept, the embodiment of the invention also provides a wavefront sub-field curvature sensing device, and as the principle of solving the problem of the wavefront sub-field curvature sensing device is similar to that of the wavefront sub-field curvature sensing method, the implementation of the wavefront sub-field curvature sensing device can refer to the implementation of the wavefront sub-field curvature sensing method, and repeated parts are not repeated.
In specific implementation, the wavefront subfield curvature sensing device provided by the embodiment of the present invention, as shown in fig. 5, specifically includes:
the split spherical mirror 11 is used for receiving and reflecting parallel light returned by a sample arm in the self-adaptive OCT system;
the image acquisition module 12 is used for receiving the reflected parallel light, and respectively acquiring sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times to obtain a light intensity distribution pattern;
the network training module 13 is used for training a neural network by taking the subtraction of the two light intensity distribution patterns obtained each time as input and taking the coefficient of the intrinsic Zernike polynomial as output;
the wave front information fitting module 14 is used for obtaining distorted whole wave front information through trained neural network nonlinear fitting according to the bilateral symmetry of human eye aberration;
and an aberration correction module 15, configured to use the obtained wavefront information as feedback to correct aberration by adjusting a deformable mirror in the adaptive OCT system, so as to obtain diffraction limit imaging.
In the wavefront field curvature sensing device provided by the embodiment of the invention, the interaction between the split spherical mirror and the four modules is combined with the wavefront sensing technology and the machine learning algorithm, so that the rapid aberration measurement and the chromatic aberration-free correction in the imaging process of the adaptive OCT are improved, the tissue interference is reduced, the diffraction limit imaging is realized, the imaging capability of the adaptive OCT is improved, the influence of the error between the optical path and the eye is reduced, and the robustness is improved.
In specific implementation, in the wavefront subfield curvature sensing device provided in the embodiment of the present invention, the wavefront subfield curvature sensing device may further include: the spectroscope or the reflector is used for receiving the parallel light reflected by the split spherical mirror and reflecting the parallel light to the image acquisition module.
In specific implementation, in the wavefront subfield curvature sensing device provided in the embodiment of the present invention, the image acquisition module may be a CCD camera; in practical applications, the CCD camera may be moved by a guide rail installed therebelow.
For more specific working processes of the modules, reference may be made to corresponding contents disclosed in the foregoing embodiments, and details are not repeated here.
Based on the same inventive concept, an embodiment of the present invention further provides an adaptive OCT system, as shown in fig. 6, including: the system comprises a low-coherence light source 1 for providing weak coherent light, a fiber coupler 2, a reference arm 3, a sample arm and a spectrometer 4 which are connected with each other through optical fibers; the sample arm comprises a first spectroscope 10, a deformable mirror 20 and a scanning mechanism 30, and further comprises the wavefront subfield curvature sensing device 40 provided by the embodiment of the invention; wherein,
the optical fiber coupler 2 is used for dividing weak coherent light into a first light beam and a second light beam, the first light beam enters the sample arm, and the second light beam enters the reference arm 3;
the reference arm 3 is used for returning the first light beam to the optical fiber coupler 2 after being reflected;
the sample arm is used for focusing the second light beam to the deformable mirror 20 through the first spectroscope 10, reflecting the second light beam to the scanning mechanism 30 through the deformable mirror 20, scanning the fundus to be detected through the scanning mechanism 30, reflecting the scanned light beam backwards to return along the original path, dividing the scanned light beam into two parts after reaching the first spectroscope 10, reflecting one part to the wavefront field curvature sensing device 40 to obtain the distorted whole wavefront information, using the obtained wavefront information as feedback, correcting aberration by adjusting the deformable mirror 20 in the self-adaptive OCT system, and enabling the other part to enter the fiber coupler 2;
and the spectrometer 4 is used for receiving the light reflected by the reference arm 3 and the sample arm and collecting an interference pattern.
Specifically, the method adopts a basic framework of frequency Domain Optical coherence tomography (SDOCT), weak infrared laser penetrates through the subcutaneous tissue of the fundus to be detected, different tissue layers interfere with each other after Optical signals are refracted due to structural differences, and the Optical signals are returned to an Optical host to recombine fundus images to be detected through an algorithm. The SDOCT system can obtain the characteristic information of all depth positions without longitudinal scanning, has high imaging speed, high imaging capacity due to the arrangement of the wavefront subfield curvature sensing device, small influence of errors of an optical path and eyes, high robustness, corrected finally obtained interference patterns, no chromatic aberration and high accuracy.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device and the system disclosed by the embodiment correspond to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The embodiment of the invention provides a wavefront sub-field curvature sensing method and device and a self-adaptive OCT system, comprising the following steps: the split spherical mirror receives and reflects parallel light returned by a sample arm in the self-adaptive OCT system; the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times respectively to obtain a light intensity distribution pattern; the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes an intrinsic Zernike polynomial coefficient as output to train a neural network; the wave front information fitting module obtains distorted whole wave front information through trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration; the aberration correction module takes the obtained wavefront information as feedback, and corrects aberration by adjusting a deformable mirror in the adaptive OCT system to acquire diffraction limit imaging. The method combines the wavefront sensing technology and the machine learning algorithm, estimates the wavefront curvature change through the light intensity distribution of the split spherical mirror before and after focus images, calculates the wavefront information through the nonlinear fitting of the neural network, corrects the aberration through the wavefront information, improves the rapid aberration measurement and the correction without chromatic aberration in the imaging process of the self-adaptive OCT, reduces the tissue interference, realizes the diffraction limit imaging, can rapidly improve the imaging capability of the self-adaptive OCT, reduces the influence of the error of an optical path and eyes, improves the robustness, and has good application prospect.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The wavefront subfield curvature sensing method and device and the adaptive OCT system provided by the present invention are described in detail above, and a specific example is applied in the present document to explain the principle and the implementation of the present invention, and the description of the above embodiment is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A wavefront subfield curvature sensing method for an adaptive OCT system, comprising:
the split spherical mirror receives and reflects parallel light returned by a sample arm in the self-adaptive OCT system;
the image acquisition module receives the reflected parallel light and acquires sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times respectively to obtain a light intensity distribution pattern;
the network training module takes subtraction of two light intensity distribution patterns obtained each time as input and takes an intrinsic Zernike polynomial coefficient as output to train a neural network;
the wave front information fitting module obtains distorted whole wave front information through the trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration;
and the aberration correction module takes the obtained wavefront information as feedback and corrects aberration by adjusting a deformable mirror in the adaptive OCT system so as to acquire diffraction limit imaging.
2. The method for sensing the curvature of the wavefront subfield according to claim 1, wherein the step of respectively acquiring far-field images of the sample arm having the same defocus amount at both sides of the focal plane comprises:
and respectively acquiring far-field images of the sample arm with the same defocusing amount on two sides of a focal plane by a single exposure mode.
3. The method of wavefront subfield curvature sensing of claim 2, where the neural network uses wavelet functions as hidden layer activation functions.
4. The method of wavefront subfield curvature sensing of claim 3, further comprising:
the spectroscope or the reflector receives the parallel light reflected by the split spherical mirror and reflects the parallel light to the image acquisition module.
5. The method for sensing curvature of a wavefront divisional field of view of claim 1, wherein the image capture module is a CCD camera.
6. The method of claim 5, wherein the image capture module is moved by a rail mounted underneath the image capture module.
7. A wavefront subfield curvature sensing device, comprising:
the split spherical mirror is used for receiving and reflecting parallel light returned by a sample arm in the self-adaptive OCT system;
the image acquisition module is used for receiving the reflected parallel light and respectively acquiring sample arm far-field images with the same defocusing amount on two sides of a focal plane for multiple times to obtain a light intensity distribution pattern;
the network training module is used for training a neural network by taking subtraction of two obtained light intensity distribution patterns as input and taking an intrinsic Zernike polynomial coefficient as output;
the wave front information fitting module is used for obtaining distorted whole wave front information through the trained neural network nonlinear fitting according to the left-right symmetry of human eye aberration;
and the aberration correction module is used for taking the obtained wavefront information as feedback and correcting aberration by adjusting a deformable mirror in the adaptive OCT system so as to acquire diffraction limit imaging.
8. The wavefront subfield curvature sensing device of claim 7, further comprising:
the spectroscope or the reflector is used for receiving the parallel light reflected by the split spherical mirror and reflecting the parallel light to the image acquisition module.
9. The wavefront subfield curvature sensing device of claim 8, wherein the image acquisition module is a CCD camera; the CCD camera moves through a guide rail installed below the CCD camera.
10. An adaptive OCT system, comprising: the low-coherence light source, the optical fiber coupler, the reference arm, the sample arm and the spectrometer are connected with each other through optical fibers; the sample arm comprises a first spectroscope, a deformable mirror, a scanning mechanism and further comprises the wavefront subfield curvature sensing device according to any one of claims 7 to 9; wherein,
the fiber coupler is used for dividing the weak coherent light into a first light beam and a second light beam, wherein the first light beam enters the sample arm, and the second light beam enters the reference arm;
the reference arm is used for returning the first light beam to the optical fiber coupler after being reflected;
the sample arm is used for focusing the second light beam to the deformable mirror through the first beam splitter, reflecting the second light beam to the scanning mechanism through the deformable mirror, scanning the fundus to be detected through the scanning mechanism, reflecting the scanned light beam backwards, returning the light beam along the original path, dividing the light beam into two parts after reaching the first beam splitter, reflecting one part of the light beam to the wavefront field curvature sensing device to obtain distorted whole wavefront information, using the obtained wavefront information as feedback, correcting aberration by adjusting the deformable mirror in the adaptive OCT system, and enabling the other part of the light beam to enter the optical fiber coupler;
and the spectrometer is used for receiving the light reflected by the reference arm and the sample arm and collecting an interference pattern.
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