CN111627085A - Wavefront sub-field curvature sensing method and device and self-adaptive OCT system - Google Patents

Abstract

The present application discloses a wavefront split field of view curvature sensing method and device, and an adaptive OCT system, including: a split spherical mirror receives the parallel light returned by a sample arm in the adaptive OCT system and reflects it; The parallel light is obtained, and the far-field images of the sample arm with the same defocus amount on both sides of the focal plane are collected multiple times to obtain the light intensity distribution pattern; the network training module subtracts the two light intensity distribution patterns obtained each time as Input, take the intrinsic Zernike polynomial coefficients as output to train the neural network; the wavefront information fitting module obtains the entire wavefront information through the nonlinear fitting of the neural network according to the left and right symmetry of the human eye aberration; the aberration correction module will The wavefront information is used as feedback to correct aberrations by adjusting the deformable mirror to obtain diffraction-limited imaging. The present application combines the wavefront sensing technology and the machine learning algorithm, which can improve the imaging capability of the adaptive OCT and reduce the influence of the optical path and the error of the eye itself.

Description

A wavefront subfield curvature sensing method and device, and an adaptive OCT system

technical field

The invention relates to the technical field of optical imaging, in particular to a method and device for sensing the curvature of a wavefront subfield of view, and an adaptive OCT system.

Background technique

Optical Coherence Tomography (OCT) is a new imaging technology based on optical coherence characteristics. The internal structure of the tomography is obtained, and the tissue characteristics of the optical tomography image are obtained to determine the target to be identified for diagnosis. Compared with conventional imaging methods, OCT technology has unique advantages. Its imaging effect is close to pathology, and it has the advantages of non-invasive and non-radiation, real-time observation of living body, high resolution (16 microns), deep imaging in tissue, and 3D image data. At present, OCT technology has become an important tool for detecting retinal diseases.

In order to improve the lateral resolution of optical retinal imaging, adaptive optics (AO) and OCT are usually combined. However, in the existing adaptive OCT (AO-OCT) technology, the uniformity of the wavefront sensing pupil illumination is relatively large. , has the disadvantages of easy pupil inclination, large dispersion influence, insufficient range, and low solution robustness.

Therefore, how to improve the imaging capability of adaptive OCT is a technical problem to be solved urgently by those skilled in the art.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present invention is to provide a wavefront subfield curvature sensing method and device, and an adaptive OCT system, which can improve the imaging capability of adaptive OCT, reduce the influence of errors between the optical path and the eye itself, and improve robustness sex. Its specific plan is as follows:

A wavefront subfield curvature sensing method for an adaptive OCT system, comprising:

The split spherical mirror receives and reflects the parallel light returned from the sample arm in the adaptive OCT system;

The image acquisition module receives the reflected parallel light, and collects far-field images of the sample arm with the same defocus amount on both sides of the focal plane for multiple times to obtain a light intensity distribution pattern;

The network training module takes the subtraction of the two light intensity distribution patterns obtained each time as the input, and takes the intrinsic Zernike polynomial coefficients as the output to train the neural network;

The wavefront information fitting module obtains the entire wavefront information of the distortion through nonlinear fitting of the trained neural network according to the left-right symmetry of the human eye aberration;

The aberration correction module uses the obtained wavefront information as feedback, and corrects the aberration by adjusting the deformable mirror in the adaptive OCT system to obtain diffraction-limited imaging.

Preferably, in the above-mentioned wavefront subfield-of-view curvature sensing method provided by the embodiment of the present invention, the far-field images of the sample arm with the same defocus amount on both sides of the focal plane are respectively collected, which specifically includes:

The far-field images of the sample arm with the same defocus amount on both sides of the focal plane are collected by a single exposure.

Preferably, in the above-mentioned wavefront sub-field of view curvature sensing method provided by the embodiment of the present invention, the neural network uses a wavelet function as the activation function of the hidden layer.

Preferably, in the above-mentioned wavefront sub-field of view curvature sensing method provided in the embodiment of the present invention, the method further includes:

A beam splitter or a reflector receives the parallel light reflected by the split spherical mirror and reflects the parallel light to the image acquisition module.

Preferably, in the above-mentioned wavefront sub-field of view curvature sensing method provided by the embodiment of the present invention, the image acquisition module is a CCD camera.

Preferably, in the above-mentioned wavefront subfield of view curvature sensing method provided by the embodiment of the present invention, the image acquisition module is moved through a guide rail installed below the image acquisition module.

An embodiment of the present invention also provides a wavefront subfield of view curvature sensing device, including:

A split spherical mirror for receiving and reflecting the parallel light returned from the sample arm in the adaptive OCT system;

The image acquisition module is used for receiving the reflected parallel light, and collecting far-field images of the sample arm with the same defocus amount on both sides of the focal plane for multiple times to obtain a light intensity distribution pattern;

The network training module is used to take the subtraction of the two light intensity distribution patterns obtained each time as input, and take the intrinsic Zernike polynomial coefficients as output to train the neural network;

The wavefront information fitting module is used to obtain the entire wavefront information of the distortion through nonlinear fitting of the trained neural network according to the left-right symmetry of the human eye aberration;

The aberration correction module is configured to use the obtained wavefront information as feedback, and correct the aberration by adjusting the deformable mirror in the adaptive OCT system, so as to obtain diffraction-limited imaging.

Preferably, in the above-mentioned wavefront sub-field of view curvature sensing device provided in the embodiment of the present invention, it further includes:

A beam splitter or a reflector, configured to receive the parallel light reflected by the split spherical mirror and reflect the parallel light to the image acquisition module.

Preferably, in the above-mentioned wavefront sub-field of view curvature sensing device provided by the embodiment of the present invention, the image acquisition module is a CCD camera; the CCD camera moves through a guide rail installed below the CCD camera.

The embodiment of the present invention also provides an adaptive OCT system, comprising: a low-coherence light source for providing weakly coherent light, an optical fiber coupler, a reference arm, a sample arm and a spectrometer, which are connected to each other through an optical fiber; the sample arm It includes a first beam splitter, a deformable mirror, and a scanning mechanism, and also includes the above-mentioned wavefront split field of view curvature sensing device provided in the embodiment of the present invention; wherein,

the optical fiber coupler for dividing the weakly coherent light into a first beam and a second beam, the first beam entering the sample arm, and the second beam entering the reference arm;

the reference arm, used for returning the first beam back to the 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, reflected by the deformable mirror to the scanning mechanism, and scanning the fundus to be measured by the scanning mechanism, The scanned light is reflected back and returns along the original path, and is divided into two parts after reaching the first beam splitter, and one part is reflected to the wavefront sub-field of view curvature sensing device to obtain the distorted whole wavefront information. The obtained wavefront information is used as feedback to correct aberrations by adjusting the deformable mirror in the adaptive OCT system, and the other part enters the fiber coupler;

The spectrometer is configured to receive light reflected back from the reference arm and the sample arm, and collect interference patterns.

It can be seen from the above technical solutions that the method and device for sensing the curvature of the wavefront subfield of view and the adaptive OCT system provided by the present invention include: a split spherical mirror receives parallel light returned from a sample arm in the adaptive OCT system and reflect; the image acquisition module receives the reflected parallel light, and collects the far-field images of the sample arm with the same defocus on both sides of the focal plane for multiple times to obtain the light intensity distribution pattern; the network training module obtains the light intensity distribution pattern each time. The two light intensity distribution patterns are subtracted as input, and the intrinsic Zernike polynomial coefficient is used as output to train the neural network; the wavefront information fitting module, according to the left-right symmetry of the human eye aberration, uses the trained neural network nonlinearity The entire wavefront information of the distortion is obtained by fitting; the aberration correction module uses the obtained wavefront information as feedback, and corrects the aberration by adjusting the deformable mirror in the adaptive OCT system to obtain diffraction-limited imaging.

The invention 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 the focus image, and solves the wavefront information through the nonlinear fitting of the neural network to obtain The wavefront information corrects aberrations, improves fast aberration measurement and chromatic aberration-free correction in the process of adaptive OCT imaging, reduces tissue interference, and realizes diffraction-limited imaging, which can quickly improve the imaging capability of adaptive OCT, reduce optical path and The influence of the error of the eye itself improves the robustness and has a good application prospect.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention or related technologies, the following briefly introduces the accompanying drawings required for the description of the embodiments or related technologies. Obviously, the accompanying drawings in the following description are only the For the embodiments of the invention, for those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without any creative effort.

FIG. 1 is a flowchart of a method for sensing curvature of wavefront subfield of view provided by an embodiment of the present invention;

2 is a schematic diagram of light transmission between a split spherical mirror and a CCD camera provided by an embodiment of the present invention;

3 is a schematic diagram of a curvature sensing provided by an embodiment of the present invention;

4 is a schematic diagram of a data solution provided by an embodiment of the present invention;

5 is a schematic structural diagram of a wavefront subfield of view curvature sensing device provided by an embodiment of the present invention;

FIG. 6 is a schematic structural diagram of an adaptive OCT system provided by an embodiment of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

The present invention provides a method for sensing the curvature of a wavefront subfield of view, as shown in FIG. 1 , comprising the following steps:

S101, the split spherical mirror receives the parallel light returned from the sample arm in the adaptive OCT system and reflects it;

It should be noted that the split spherical mirror divides the standard spherical mirror into two halves, that is to say, the split spherical mirror is divided into two parts. Figure 2 shows the structure of the split spherical mirror 11, which can be imaged before and after the focus respectively;

S102, the image acquisition module receives the reflected parallel light, and collects far-field images of the sample arm with the same defocus amount on both sides of the focal plane (ie, before and after the focus), respectively, to obtain a light intensity distribution pattern;

During specific implementation, as shown in FIG. 2 , the image acquisition module 12 may be a CCD camera. In practical applications, the image acquisition module 12 can be moved through the guide rail installed below it, that is, when the parallel light reflected by the split spherical mirror enters the CCD camera, the movement of the guide rail can ensure that two images are one in front and the other behind. ;

S103, the network training module takes the subtraction of the two light intensity distribution patterns obtained each time as the input, and takes the intrinsic Zernike polynomial coefficients as the output to train the neural network;

It should be noted that when increasing the fitting order, there is a serious problem of lack of rank. In other words, the same result can be achieved with fewer orders. Previously, due to the strong linear correlation, in order to fit some frequency components If they are combined, a very high order needs to be improved, and an excessively high order will cause the matrix to be ill-conditioned. The current highest fitting can only use orders 16 to 18 or use nonlinear optimization to process the results. The present invention solves this problem by using "eigenmodes", that is, the Zernike polynomials on the semi-circular aperture are orthogonalized, and the eigenmodes are used based on the substrate, and the aberrations are expressed by the coefficients of the eigenZernike polynomials;

S104, the wavefront information fitting module obtains the entire distorted wavefront information through nonlinear fitting of the trained neural network according to the left-right symmetry of the human eye aberration;

S105 , the aberration correction module uses the obtained wavefront information as feedback, and corrects the aberration by adjusting the deformable mirror in the adaptive OCT system to obtain diffraction-limited imaging.

In the above-mentioned wavefront sub-field of view curvature sensing method provided by the embodiment of the present invention, the wavefront sensing technology and the machine learning algorithm are combined, and the wavefront curvature is estimated by the light intensity distribution of the split spherical mirror in the pre-focus and after-focus images The wavefront information is solved by nonlinear fitting of the neural network, and the aberration is corrected with the wavefront information, which improves the fast aberration measurement and chromatic aberration correction in the adaptive OCT imaging process, reduces tissue interference, and realizes diffraction. Extreme imaging, which can quickly improve the imaging capability of adaptive OCT, reduce the influence of errors between the optical path and the eye itself, improve robustness, and have good application prospects.

Taking FIG. 3 as an example below, the curvature sensing principle of the above-mentioned wavefront subfield of view curvature sensing method provided by the embodiment of the present invention will be described in detail:

The curvature of the wavefront at the pupil changes locally, and the light intensity distribution of the corresponding in-focus and out-of-focus images will change accordingly. According to the transmission equation of the near-field electromagnetic wave, the wavefront information can be solved, as shown in equation (1):

为强度，

为相位，▽为梯度算子，得到的结果为斜率，▽²为拉普拉斯算子，得到的结果为曲率。

为光瞳内坐标，

为像面内的光瞳坐标，在上式中默认γ＝1。可见，其结果与斜率曲率均有关。in,

is the strength,

is the phase, ▽ is the gradient operator, the result is the slope, ▽ ² is the Laplace operator, and the result is the curvature.

is the inner pupil coordinate,

is the pupil coordinate in the image plane, and γ=1 by default in the above formula. It can be seen that the results are related to the slope curvature.

For adaptive optics systems, the defocus amount is generally only a few focal depths, and the defocused star image is very close to the pupil shape. After subtraction, it can be considered that:

where R is the radius of the light spot.

Therefore, formula (1) can be obtained by approximation formula (2):

Among them, P ₁ and P ₂ are two symmetrical planes with a defocus amount l on both sides of the focal plane, and Δz is the distance between the conjugate position of P ₁ and P ₂ relative to the entrance pupil, as shown in equation (3):

Δz=f(f-l)/l (3)

带入式(2)可以得到式(4)。Assume

Substituting equation (2) into equation (4) can be obtained.

For equation (4), the Poisson equation can be solved, and the deformable mirror in the adaptive OCT system can automatically converge to the surface shape that satisfies the Poisson equation; estimate.

Fast Fourier Transform

So you can get:

在P₂位置所得到的光强分布为

Taking P ₁ as an example, the conversion relationship between the focal plane and the pupil plane is shown in formula (6), and the light intensity distribution obtained at the position of P ₁ according to the conversion relationship is:

_The resulting light intensity distribution at the P2 position is

During specific implementation, in the above-mentioned wavefront subfield-of-view curvature sensing method provided by the embodiment of the present invention, the far-field images of the sample arm with the same defocus amount on both sides of the focal plane are respectively collected, which specifically includes: The far-field images of the sample arm with the same defocus amount on both sides of the focal plane were collected by the single-shot method. This method can realize the acquisition of front and rear images without moving parts, and realize simultaneous measurement. Using the characteristics of small influence of the curvature sensor aperture, based on the sub-field detection of the extended target of the fundus, the final result is obtained through the synthesis algorithm. Full wavefront distortion information.

During specific implementation, in the above-mentioned wavefront sub-field of view curvature sensing method provided by the embodiment of the present invention, the neural network may use a wavelet function as the activation function of the hidden layer. Such a wavelet neural network combines the characteristics of multi-scale representation of wavelet transform, and at the same time retains the characteristics of good generalization ability and strong nonlinear mapping ability of neural network.

What needs to be understood is that machine learning is a branch of artificial intelligence. Its purpose is to learn independently from a large amount of empirical data, inductively discover the relationship between variables in the system, summarize and use algorithms to continuously improve the weight value, and finally carry out the analysis of unknown data. predict. When the existing rules and formulas cannot describe common aberrations and systematic errors, the establishment of machine learning models to process large amounts of data shows great flexibility and adaptability. As shown in FIG. 4 , the present invention first rotates the two light intensity distribution patterns, then aligns them, and then performs subtraction. The two light intensity distribution patterns after the subtraction are used as input, and the intrinsic Zernike polynomial coefficient is Output, train the neural network.

In addition, it should be noted that the present invention builds a system error (gravity, temperature, airflow, vibration, actuator error, optical element surface error, polarization error, light intensity flicker) model “end-to-end” based on a deep learning algorithm , to realize the standard calibration of the system and reduce the pressure of hardware implementation.

During specific implementation, in the above-mentioned wavefront split field of view curvature sensing method provided by the embodiment of the present invention, the method may further include: a beam splitter or a reflector receives the parallel light reflected by the split spherical mirror and reflects the parallel light to an image acquisition module.

Based on the same inventive concept, an embodiment of the present invention also provides a wavefront subfield of view curvature sensing device, because the principle of solving the problem of the wavefront subfield of view curvature sensing device is the same as the aforementioned wavefront subfield of view curvature sensor. The sensing methods are similar, so the implementation of the wavefront sub-field of view curvature sensing device can refer to the implementation of the wavefront sub-field of view curvature sensing method, and the repetition will not be repeated.

During specific implementation, the wavefront subfield of view 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 to receive and reflect the parallel light returned from the sample arm in the adaptive OCT system;

The image acquisition module 12 is used for receiving the reflected parallel light, and collecting far-field images of the sample arm with the same defocus amount on both sides of the focal plane for multiple times to obtain a light intensity distribution pattern;

The network training module 13 is used for taking the subtraction of the two light intensity distribution patterns obtained each time as the input, and taking the intrinsic Zernike polynomial coefficients as the output to train the neural network;

The wavefront information fitting module 14 is used to obtain the entire wavefront information of the distortion through nonlinear fitting of the trained neural network according to the left-right symmetry of the human eye aberration;

The aberration correction module 15 is configured to use the obtained wavefront information as feedback to correct the aberration by adjusting the deformable mirror in the adaptive OCT system, so as to obtain diffraction-limited imaging.

In the above-mentioned wavefront sub-field of view curvature sensing device provided by the embodiment of the present invention, the adaptive OCT imaging process can be improved through the interaction of the split spherical mirror and the above four modules, combined with the wavefront sensing technology and the machine learning algorithm Fast aberration measurement and chromatic aberration-free correction in the device can reduce tissue interference and achieve diffraction-limited imaging, thereby improving the imaging capability of adaptive OCT, reducing the influence of errors between the optical path and the eye itself, and improving robustness.

During specific implementation, in the above-mentioned wavefront split field of view curvature sensing device provided by the embodiment of the present invention, it may further include: a beam splitter or a reflector for receiving the parallel light reflected by the split spherical mirror and converting the parallel light reflected to the image acquisition module.

In specific implementation, in the above-mentioned wavefront sub-field of view curvature sensing device provided by 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 below it.

For more specific working processes of the above-mentioned modules, reference may be made to the corresponding contents disclosed in the foregoing embodiments, which will not be repeated here.

Based on the same inventive concept, an embodiment of the present invention also provides an adaptive OCT system, as shown in FIG. 6 , including: a low-coherence light source 1 for providing weakly coherent light, a fiber coupler 2, a reference arm 3, and a sample arm and the spectrometer 4, which are connected to each other by optical fibers; the sample arm includes a first beam splitter 10, a deformable mirror 20, a scanning mechanism 30, and also includes the above-mentioned wavefront division field of view curvature sensing device 40 provided in the embodiment of the present invention; wherein,

The fiber coupler 2 is used to divide the weakly coherent light into a first beam and a second beam, the first beam enters the sample arm, and the second beam enters the reference arm 3;

The reference arm 3 is used to return the first beam to the optical fiber coupler 2 after being reflected;

The sample arm is used to focus the second light beam to the deformable mirror 20 through the first beam splitter 10, and is reflected by the deformable mirror 20 to the scanning mechanism 30. The scanning mechanism 30 scans the fundus to be tested, and the scanned light is reflected back along the original direction. After reaching the first beam splitter 10, it is divided into two parts, one part is reflected to the wavefront sub-field of view curvature sensing device 40 to obtain the distorted whole wavefront information, and the obtained wavefront information is used as feedback. The deformable mirror 20 in the OCT system is adapted to correct the aberration, and the other part enters the fiber coupler 2;

The spectrometer 4 is used for receiving the light reflected from the reference arm 3 and the sample arm, and collecting the interference pattern.

Specifically, the present invention adopts the basic structure of Spectral Domain Optical Coherence Tomography (SDOCT), and uses weak infrared laser light to penetrate the subcutaneous tissue of the fundus to be measured. After the host computer, the fundus image to be tested is reconstructed by algorithm. The SDOCT can obtain the feature information of all depth positions without longitudinal scanning, the imaging speed is fast, and due to the setting of the wavefront sub-field of view curvature sensing device, the imaging capability is high, and the influence of the error between the optical path and the eye itself is small. High, the final obtained interference pattern is corrected, free of chromatic aberration, and high accuracy.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments may be referred to each other. For the devices and systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and reference may be made to the descriptions of the methods for related parts.

Professionals may further realize that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two, in order to clearly illustrate the possibilities of hardware and software. Interchangeability, the above description has generally described the components and steps of each example in terms of functionality. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

The steps of a method or algorithm described in conjunction with the embodiments disclosed herein may be directly implemented in hardware, a software module executed by a processor, or a combination of the two. A software module can be placed in random access memory (RAM), internal memory, read only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other in the technical field. in any other known form of storage medium.

An embodiment of the present invention provides a wavefront split field of view curvature sensing method and device, and an adaptive OCT system, including: a split spherical mirror receives parallel light returned from a sample arm in the adaptive OCT system and reflects it; an image acquisition module Receive the reflected parallel light, and collect the far-field images of the sample arm with the same defocus on both sides of the focal plane for multiple times to obtain the light intensity distribution pattern; the network training module uses the two light intensity distribution patterns obtained each time. Subtraction is the input, and the intrinsic Zernike polynomial coefficient is used as the output to train the neural network; the wavefront information fitting module obtains the entire distorted wave by nonlinear fitting of the trained neural network according to the left and right symmetry of the human eye aberration. The aberration correction module uses the obtained wavefront information as feedback, and corrects the aberration by adjusting the deformable mirror in the adaptive OCT system to obtain diffraction-limited imaging. In this way, the wavefront sensing technology and machine learning algorithm are combined, and the wavefront curvature change is estimated by the light intensity distribution of the split spherical mirror in the pre-focus and after-focus images, and the wavefront information is solved by nonlinear fitting of the neural network. The former information corrects aberrations, improves fast aberration measurement and chromatic aberration correction in the process of adaptive OCT imaging, reduces tissue interference, and realizes diffraction-limited imaging, which can quickly improve the imaging capability of adaptive OCT and reduce the optical path and the eye itself. The influence of the error can improve the robustness, and the application prospect is good.

Finally, it should also be noted that in this document, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or that there is any such actual relationship or sequence between operations. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device that includes a list of elements includes not only those elements, but also includes not explicitly listed or other elements inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

The wavefront sub-field curvature sensing method and device and the adaptive OCT system provided by the present invention have been described in detail above. Specific examples are used in this paper to illustrate the principles and implementations of the present invention. It is only used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific embodiments and application scope. In summary, The contents of this specification should not be construed as limiting 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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