Lamination imaging method, device, equipment, medium and product
By using circular probes in the iterative phase recovery algorithm to collect diffraction sub-maps, guess and edge error removal, the problem of edge error impact during the iteration process is solved, and rapid convergence and high-quality imaging are achieved.
Patent Information
- Application Number
- CN202411536516.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2025-02-25
AI Technical Summary
The existing iterative phase recovery algorithms are easily affected by edge error information during the iteration process. The iterative calculations are huge and the convergence speed is slow, which limits the application of the algorithm.
By collecting all diffraction sub-maps of the sample to be recovered based on the circular probe, the guessing object field image and the circular probe are restored, the edge area error information of the initial restored image is eliminated, and the target restored image is obtained, thereby accelerating the convergence process.
The artifact phenomenon caused by error information is reduced, the imaging quality is improved, and rapid convergence and high-quality imaging are achieved.
Smart Images
Figure CN119516019A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of imaging technology, and in particular to a stacked imaging method, device, equipment, medium and product. Background Art
[0002] In optical imaging, usually only the intensity of the light wave (i.e., the light intensity distribution) can be directly measured, while the phase information is difficult to obtain directly. Therefore, the existing iterative phase retrieval algorithm uses the mathematical inverse problem of estimating the phase using the light intensity distribution. It combines the traditional CDI (Coherent Diffractive Imaging) with the reconstruction method based on overlapping scanning to produce a phase retrieval technology with an expandable imaging range, which has been widely used. The goal of phase recovery is to recover the complete complex amplitude distribution from the known light intensity distribution, that is, to recover the light intensity distribution information and phase information at the same time.
[0003] However, the existing iterative phase recovery algorithm is easily affected by edge error information during the iteration process, has huge iterative calculation amount and slow convergence speed, which greatly limits the application of the algorithm. Summary of the invention
[0004] The purpose of the present application is to provide a stacked imaging method, device, equipment, medium and product, which can solve the problems of slow convergence speed and poor imaging quality of stacked imaging.
[0005] To achieve the above objectives, this application provides the following solutions:
[0006] In a first aspect, the present application provides a stacked imaging method, comprising:
[0007] Based on the circular probe, all diffraction sub-images of the sample to be restored are collected; the diffraction sub-images are the real light intensity distribution information of the sample to be restored;
[0008] The light intensity distribution of the sample to be restored and the circular probe are guessed respectively to obtain a guessed object field image and a guessed circular probe; the object field image includes sample areas corresponding to the positions of the respective diffraction sub-images;
[0009] According to the current random order, each diffraction sub-image is restored based on the guessed object field image and the guessed circular probe to obtain an initial restored image; the current random order is a restoration order in which all diffraction sub-images are updated once;
[0010] According to a preset threshold and the radius of the guessed circular probe, the error information of the edge area of each of the initial restored images is eliminated to obtain each target restored image; wherein the preset threshold is smaller than the radius of the guessed circular probe; the edge area is an annular area between a circle formed with the center of the circular probe as the center and the preset threshold as the radius, and a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe;
[0011] According to each target restoration image, a restoration image of the sample to be restored is determined.
[0012] In a second aspect, the present application provides a laminated imaging device, comprising:
[0013] A circular probe is used to collect all diffraction sub-images of the sample to be restored; the diffraction sub-images are the real light intensity distribution information of the sample to be restored;
[0014] A guessing module, used to guess the light intensity distribution of the sample to be restored and the circular probe respectively, to obtain a guessed object field image and a guessed circular probe; the object field image includes sample areas corresponding to the positions of the respective diffraction sub-images;
[0015] A restoration module, used to restore each diffraction sub-image according to the guessed object field image and the guessed circular probe in accordance with a current random order to obtain an initial restored image; the current random order is a restoration order in which all diffraction sub-images are updated once;
[0016] A removal module is used to remove error information of the edge area of each of the initial restored images according to a preset threshold and the radius of the guessed circular probe to obtain each target restored image; wherein the preset threshold is smaller than the radius of the guessed circular probe; the edge area is an annular area between a circle formed with the center of the circular probe as the center and the preset threshold as the radius, and a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe;
[0017] The determination module is used to determine the restored image of the sample to be restored according to each target restored image.
[0018] In a third aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-mentioned stacked imaging method.
[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above-mentioned stacked imaging method when executed by a processor.
[0020] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the steps of the above-mentioned stacked imaging method when executed by a processor.
[0021] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0022] The present application provides a stacked imaging method, device, equipment, medium and product. Based on a stacked imaging system, all diffraction sub-images of a sample to be restored are collected to obtain the real light intensity distribution information of the sample to be restored, and then the light intensity distribution of the sample to be restored is obtained according to the guessed object field image, and each diffraction sub-image is restored by using the guessed circular probe to obtain an initial restored image, and then the error information of the edge area of each of the initial restored images is removed according to the current random order, the preset threshold and the radius of the guessed circular probe to obtain each target restored image. Thus, the error information of the edge area of each diffraction sub-image is filtered out at the initial stage of updating, thereby accelerating the convergence speed of stacked imaging. Since the error information is eliminated during the iteration process, the artifact phenomenon caused by the error information is reduced, and the imaging quality of each target restored image is greatly improved. The restored image of the sample to be restored determined by the present application according to each target restored image has a fast imaging speed and high imaging quality, avoiding the problems of slow imaging speed and poor quality caused by a large number of iterations caused by error information in the edge area in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0024] Figure 1 A schematic diagram of a stacked imaging method provided in an embodiment of the present application;
[0025] Figure 2 An optical path diagram of a stacked imaging system in a stacked imaging method provided in an embodiment of the present application;
[0026] Figure 3 A schematic diagram of an iterative update algorithm of a stacked imaging method provided in an embodiment of the present application;
[0027] Figure 4 It is a structural block diagram of a stacked imaging device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0028] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0029] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.
[0030] like Figure 1 As shown, the present application provides a stacked imaging method, comprising:
[0031] Step 101: Based on a circular probe, all diffraction sub-images of the sample to be restored are collected; the diffraction sub-images are the real light intensity distribution information of the sample to be restored.
[0032] In some embodiments, based on a circular probe, all diffraction sub-images of the sample to be restored are collected, specifically including: using a laser to pass through the circular probe to irradiate each scanning area of the sample to be restored, to obtain a diffraction sub-image corresponding to each scanning area; using the diffraction sub-image corresponding to each scanning area as the diffraction sub-image of the sample to be restored; the overlap rate between two adjacent diffraction sub-images ranges from 70% to 80%.
[0033] Among them, a stacked imaging system is built, and the circular probe is a component in the stacked imaging system.
[0034] Reference Figure 2 The stack imaging system includes: a circular probe 21, a reflector (including reflector 1 and reflector 2), a laser 3, an attenuator 4, a spatial filter 5, a collimating lens 6, a three-dimensional translation stage 8 for fixing the sample to be restored, and a detector 9 (Charge-coupled Device, CCD).
[0035] Among them, a circular probe 21 with a radius of 1800 pixels is selected. The model of the detector is IGV-B4020M-KF000, and the pixel size is 2.4um. Using a 5×5 scanning method, the diffraction distance from the sample to be restored to the detector 9 that collects the diffraction sub-image is 135mm. The diffraction sub-image collected by the detector 9 will be transmitted to the computer for stacked imaging restoration. The laser 3 uses a helium-neon laser or a red light laser with a wavelength of 632.8nm.
[0036] The experimental process of the stacked imaging system is as follows: the laser emitted by the helium-neon laser passes through the reflector 1 and the reflector 2, and the optical path can be collimated by adjusting the up, down, left, and right knobs of the reflector. Because the helium-neon laser used in the experiment cannot adjust the output power, an attenuator 4 is used behind the collimated laser to adjust the light intensity of the output light to ensure that the image received by the detector 9 is not overexposed. Since the laser spot size is too small, the light needs to be expanded through the spatial filter 5 and the collimating lens 6 to ensure uniform amplification of the light beam. The collimated and expanded laser passes through the small hole of the circular probe and irradiates each scanning area of the sample to be restored to obtain a diffraction sub-image. The diffraction sub-image is finally received by the detector 9, and then transmitted to the computer to input all the diffraction sub-images into the method provided in this application for processing.
[0037] It is worth noting that the three-dimensional translation stage 8 for fixing the sample to be restored is arranged between the circular probe 21 and the detector 8, and the three-dimensional translation stage 8 moves according to a preset trajectory to ensure that the circular probe irradiates each scanning area of the sample to be restored.
[0038] Exemplarily, a three-dimensional translation stage 8 and a circular probe are used to perform a programmed array (5×5) scan perpendicular to the optical axis plane on the sample to be restored, and the light intensity distribution information after modulation of the sample to be restored is recorded to obtain 25 diffraction sub-images, i.e., all the diffraction sub-images R(j), where j is the serial number of the diffraction sub-image, j=1, 2, 3....25.
[0039] The overlap rate of each diffraction sub-image is in the range of 70%-80%, which can ensure sufficient information redundancy for iterative constraints in the stacking reconstruction process.
[0040] Step 102: respectively guessing the light intensity distribution of the sample to be restored and the circular probe to obtain a guessed object field image and a guessed circular probe; the object field image includes sample areas corresponding to the positions of the respective diffraction sub-images.
[0041] In practical applications, a matrix of all zeros may be set as the guessed light intensity distribution information of the sample area in the object field image.
[0042] Reference Figure 3 , the sample to be restored and the circular probe 21 are guessed, and the guessed object field image Object (A) and the circle obtained based on the radius of the guessed circular probe (ie, the guessed probe P) are obtained.
[0043] Step 103: according to the current random order, each diffraction sub-image is restored according to the guessed object field image and the guessed circular probe to obtain an initial restored image; the current random order is the restoration order of all diffraction sub-images updated once.
[0044] In some embodiments, each diffraction sub-image is restored according to the guessed object field image and the guessed probe P to obtain an initial restored image, which specifically includes: obtaining the current position of the currently updated diffraction sub-image according to the current random order; extracting the sample area corresponding to the current position in the guessed object field image, and determining the incident wave according to the sample area and the guessed circular probe; the incident wave is the interaction occurring when the circular probe passes through the guessed object field image; propagating the incident wave to the frequency domain by Fresnel diffraction to determine the complex amplitude of the sample area; the complex amplitude includes sample light intensity distribution information and phase information; replacing the sample light intensity distribution information in the complex amplitude with the real light intensity distribution information of the currently updated diffraction sub-image to obtain a new complex amplitude; propagating the new complex amplitude back to the airspace through reverse Fresnel diffraction to obtain an updated complex amplitude; wherein the updated complex amplitude includes updated light intensity distribution information and updated phase information; and determining the initial restored image based on the updated complex amplitude.
[0045] Reference Figure 3 , step 1 puts the sample to be restored into the stacked imaging acquisition system; step 2 obtains all the collected diffraction sub-images through the imaging acquisition system; step 3 obtains the current position of the currently updated diffraction sub-image, i.e. R(13); step 4 uses the guessed object field image Object(A), the guessed probe P and the diffraction sub-image R(j) as the input of the iterative algorithm to start iterative update. In each iteration of the main loop, the code will randomly arrange the scanning position sequence and process each scanning position in the sub-loop. Step 5 When all the diffraction sub-images are updated once, it is considered that one iteration has been completed.
[0046] Specifically, firstly, the sample area O(13) corresponding to the current position R(13) is extracted from the guessed object field image Object(A), and then the incident wave is calculated through the convolution operation of the sample area O(13) and the guessed probe P, and the Fresnel diffraction is used to propagate it in the frequency domain to obtain the calculated complex amplitude. The calculated complex amplitude is obtained in order to obtain the light intensity distribution information of the sample area. The light intensity distribution information of the sample area is replaced with the real light intensity distribution information of the currently updated diffraction sub-image to obtain a new complex amplitude; and then it is propagated back to the airspace through the reverse Fresnel diffraction to obtain the updated complex amplitude. Then, based on the updated complex amplitude, the initial restored image is determined, that is, Figure 3 O(13A) in . According to the current random order, the above operation is performed on each diffraction sub-image one by one.
[0047] Step 104: According to a preset threshold and the guessed radius of the circular probe, the error information of the edge area of each of the initial restored images is eliminated to obtain each target restored image; wherein the preset threshold is smaller than the guessed radius of the circular probe; the edge area is an annular area between a circle with the center of the circular probe as the center and the preset threshold as the radius, and a circle with the center of the circular probe as the center and the guessed radius of the circular probe.
[0048] In some embodiments, according to a preset threshold and the guessed circular probe radius, error information of the edge area of each of the initial restored images is eliminated to obtain each target restored image, specifically including: obtaining the currently updated initial restored image; the initial restored image is a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe as the radius; shrinking the radius of the guessed circular probe to the preset threshold to obtain the initial restored image with the edge area eliminated; using the initial restored image with the edge area eliminated as the target restored image; for each initial restored image, according to the current random order, returning to the step "shrinking the guessed circular probe radius to the preset threshold to obtain the initial restored image with the edge area eliminated" to update and determine each target restored image.
[0049] Reference Figure 3 In this application, O(13A) is the initial restored image of each diffraction sub-image obtained before elimination, and O(13B) is the target restored image of each diffraction sub-image obtained after elimination, that is, O(13B) is used for the restoration of the sample to be restored. However, the prior art directly uses the restored O(13A) for the restoration of the sample to be restored. Therefore, eliminating or shrinking the edge of O(13A) to obtain O(13B) can achieve the filtering of error information, thereby reducing the large number of iterations caused by error information, and finally accelerating the convergence speed of the algorithm and improving the imaging quality.
[0050] Among them, the edge area is a circular ring area of (Rr). Therefore, the circular ring area generates error information during iteration, so it is removed; among them, r is a preset threshold.
[0051] Step 105: Determine the restored image of the sample to be restored according to each target restored image.
[0052] In some embodiments, based on each target restored image, a restored image of a sample to be restored is determined, specifically comprising: using each of the target restored images as the diffraction subimage, and restoring each diffraction subimage in a new random order until a maximum number of iterations is reached to obtain each final target restored image; wherein, during each iteration, the new random order is updated once; based on each final target restored image, a restored image of the sample to be restored is determined.
[0053] Specifically, if the maximum number of iterations is 10, each iteration is to process the above steps once for 25 diffraction patterns according to the random order generated by the computer, and stop after 10 repetitions.
[0054] In some embodiments, determining a restored image of a sample to be restored based on each final target restored image specifically includes: using a mask to insert each final target restored image into a sample area corresponding to the object field image to obtain an updated object field image, and using the updated object field image as the restored image of the sample to be restored.
[0055] In practical applications, the target restored image (O(13B)) is inserted into the guessed object field image Object(A) to obtain the updated object field image Object(B), which is regarded as completing an update of a diffraction sub-image. This process ensures that after each iteration, the corresponding sample area in the guessed object field image can be gradually updated to obtain the latest reconstruction result, that is, the restored image of the sample to be restored.
[0056] The beneficial effects that this application can achieve are:
[0057] The present application can filter out erroneous information from the inversion result (ie, the initial restored image) of each diffraction sub-image at the beginning of the iteration, thereby reducing the large number of iterations required for the error information, thereby achieving rapid convergence of the results.
[0058] This application not only tests the applicability of the sample from the simulation aspect, but also verifies the experimental results by combining different experiments (transmission, reflection, etc.) and samples of different materials (artificial samples, biological samples, etc.). The final results of the simulation and experiment show that the scheme is widely applicable to iterative stacked imaging technology.
[0059] Since the introduction of erroneous information is avoided, this solution not only improves the iteration speed but also takes into account the quality of imaging, and can obtain better imaging quality with fewer iterations.
[0060] Reference Figure 4, provides a stacked imaging device, including: a circular probe 21, used to collect all diffraction sub-images of a sample to be restored; the diffraction sub-image is the real light intensity distribution information of the sample to be restored; a guessing module 22, used to guess the light intensity distribution of the sample to be restored and the circular probe 21 respectively, to obtain a guessed object field image and a guessed circular probe; the object field image includes a sample area corresponding to the position of each diffraction sub-image; a recovery module 23, used to restore each diffraction sub-image according to the guessed object field image and the guessed circular probe in accordance with the current random order, to obtain an initial restored image; the current random order A restoration order is updated once for all diffraction sub-images; a elimination module 24 is used to eliminate the error information of the edge area of each of the initial restoration images according to a preset threshold and the radius of the guessed circular probe, so as to obtain each target restoration image; wherein the preset threshold is less than the radius of the guessed circular probe; the edge area is an annular area between a circle formed with the center of the circular probe as the center and the preset threshold as the radius, and a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe; a determination module 25 is used to determine the restoration image of the sample to be restored according to each target restoration image.
[0061] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.
[0062] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0063] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0064] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0065] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive memory (ReRdM), magnetic memory (MRdM), ferroelectric memory (FRdM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RdM) or external cache memory, etc. By way of illustration and not limitation, RdM may be in various forms, such as static random access memory (SRdM) or dynamic random access memory (DRdM).
[0066] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.
[0067] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0068] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. A stacked imaging method, characterized in that: include: Based on the circular probe, all diffraction sub-images of the sample to be restored are collected; The diffraction sub-image is the real light intensity distribution information of the sample to be restored; The light intensity distribution of the sample to be restored and the circular probe are guessed respectively to obtain a guessed object field image and a guessed circular probe; the object field image includes sample areas corresponding to the positions of the respective diffraction sub-images; According to the current random order, each diffraction sub-image is restored based on the guessed object field image and the guessed circular probe to obtain an initial restored image; the current random order is a restoration order in which all diffraction sub-images are updated once; According to a preset threshold and the radius of the guessed circular probe, the error information of the edge area of each of the initial restored images is eliminated to obtain each target restored image; wherein the preset threshold is smaller than the radius of the guessed circular probe; the edge area is an annular area between a circle formed with the center of the circular probe as the center and the preset threshold as the radius, and a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe; According to each target restoration image, a restoration image of the sample to be restored is determined.
2. The stacked imaging method according to claim 1, characterized in that: According to each target restoration image, the restoration image of the sample to be restored is determined, specifically including: Taking each of the target restored images as the diffraction subimages, and restoring each diffraction subimage in a new random order until a maximum number of iterations is reached, thereby obtaining each final target restored image; wherein the new random order is updated once during each iteration; According to each final target restored image, a restored image of the sample to be restored is determined.
3. The stacked imaging method according to claim 1, characterized in that: According to the guessed object field image and the guessed circular probe, each diffraction sub-image is restored to obtain an initial restored image, specifically including: According to the current random order, obtain the current position of the currently updated diffraction sub-image; In the guessed object field image, a sample area corresponding to the current position is extracted, and an incident wave is determined according to the sample area and the guessed circular probe; the incident wave is an interaction occurring when the circular probe passes through the guessed object field image; The incident wave is propagated to the frequency domain by using Fresnel diffraction to determine the complex amplitude of the sample area; the complex amplitude includes sample light intensity distribution information and phase information; The real light intensity distribution information of the currently updated diffraction sub-image replaces the sample light intensity distribution information in the complex amplitude to obtain a new complex amplitude; Propagate the new complex amplitude back to the airspace through reverse Fresnel diffraction to obtain an updated complex amplitude; wherein the updated complex amplitude includes updated light intensity distribution information and updated phase information; Based on the updated complex amplitude, an initial restored image is determined.
4. The stacked imaging method according to claim 1, characterized in that: According to a preset threshold and the radius of the guessed circular probe, the error information of the edge area of each of the initial restored images is eliminated to obtain each target restored image, specifically including: Acquire the currently updated initial restored image; the initial restored image is a circle formed by taking the center of the circular probe as the center and the guessed radius of the circular probe; Shrinking the radius of the guessed circular probe to the preset threshold value to obtain an initial restored image with the edge area removed; Using the initial restored image after removing the edge area as the target restored image; For each initial restored image, according to the current random order, return to the step of "shrinking the radius of the guessed circular probe to the preset threshold to obtain the initial restored image with the edge area removed" to update and determine each target restored image.
5. The stacked imaging method according to claim 2, characterized in that: According to each final target restoration image, the restoration image of the sample to be restored is determined, specifically including: Each final target restored image is inserted into a sample area corresponding to the object field image by using a mask to obtain an updated object field image, and the updated object field image is used as a restored image of the sample to be restored.
6. The stacked imaging method according to claim 1, characterized in that: Based on the circular probe, all diffraction sub-images of the sample to be restored are collected, including: Using laser light to pass through the circular probe to irradiate each scanning area of the sample to be restored, and obtaining a diffraction sub-image corresponding to each scanning area; The diffraction sub-images corresponding to each scanning area are used as the diffraction sub-images of the sample to be restored; and the overlapping rate between two adjacent diffraction sub-images is in the range of 70%-80%.
7. A laminated imaging device, characterized in that: include: A circular probe is used to collect all diffraction sub-images of the sample to be restored; the diffraction sub-images are the real light intensity distribution information of the sample to be restored; A guessing module, used to guess the light intensity distribution of the sample to be restored and the circular probe respectively, to obtain a guessed object field image and a guessed circular probe; the object field image includes sample areas corresponding to the positions of the respective diffraction sub-images; A restoration module, used to restore each diffraction sub-image according to the guessed object field image and the guessed circular probe in accordance with a current random order to obtain an initial restored image; the current random order is a restoration order in which all diffraction sub-images are updated once; A removal module is used to remove error information of the edge area of each of the initial restored images according to a preset threshold and the radius of the guessed circular probe to obtain each target restored image; wherein the preset threshold is smaller than the radius of the guessed circular probe; the edge area is an annular area between a circle formed with the center of the circular probe as the center and the preset threshold as the radius, and a circle formed with the center of the circular probe as the center and the radius of the guessed circular probe; The determination module is used to determine the restored image of the sample to be restored according to each target restored image.
8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the stacked imaging method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the stacked layer imaging method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the stacked layer imaging method according to any one of claims 1 to 6 are implemented.