OCTA image processing method and device and electronic equipment

Abstract

The invention provides an OCTA image processing method and apparatus, and an electronic device. The method comprises the steps of obtaining an OCTA image; retina area slice scanning is carried out on the OCTA image, and multiple frames of retina slice images are determined; calculating a decorrelation relation value of each frame of retina slice image and determining a self-adaptive threshold value; and for each frame of the retina slice image, when it is judged that the de-correlation relationship value of the current frame of the retina slice image exceeds an adaptive threshold value, performing three-dimensional filtering processing on the current frame of the retina slice image to obtain an artifact-removed image corresponding to the OCTA image. According to the method, the position where the white line artifacts occur is judged through calculation of the decorrelation coefficient and self-adaptive determination of the threshold value, the white line noise is smoothed in a three-dimensional filtering mode, and tiny blood vessels cannot be affected while the white line artifacts are improved.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to an OCTA image processing method, device and electronic device. Background Art

[0002] OCT (optical coherence tomography) is an imaging technology that uses interference of light to achieve micron-level depth resolution. It is also a non-contact, non-invasive diagnostic technology that can obtain clear cross-sectional images of the retina. Compared with the OCT signals of static tissues, the OCT signals of blood vessels show more fluctuations, and thus the optical coherence tomography (OCTA) technology has been developed. OCTA requires repeated A scans or B scans to record changes in spectral signals. Commonly used OCTAs include speckle variance OCTA and improved speckle contrast OCTA.

[0003] Limited by the imaging speed, the movement of the object under examination is an important reason for the generation of motion artifacts (striped noise) in the OCTA enface image. It is caused by the inevitable blood flow pulsation, breathing and voluntary movement of the subject. The positioning accuracy of the galvanometer and the mechanical jitter of the system can also cause the appearance of motion artifacts. In summary, various factors may randomly affect the imaging process and cause the appearance of motion artifacts. Motion artifacts appear as horizontal or vertical white lines (striped noise) on the OCTA top view, which seriously affects the visual quality of the image and is not conducive to subsequent processing, such as image segmentation, classification and disease diagnosis.

[0004] In order to solve the problem of motion artifacts in OCTA enface images, researchers have proposed solutions from both software and hardware aspects. However, due to cost or processing effect issues, motion artifacts cannot be improved well. Summary of the invention

[0005] The purpose of the present application is to provide an OCTA image processing method, device and electronic device, which utilizes the three-dimensional decorrelation signal in the OCTA blood flow generation algorithm to determine the location where the white line artifact occurs, and then uses three-dimensional filtering to smooth the white line noise at the white line location, thereby improving the white line artifact without affecting the tiny blood vessels.

[0006] In a first aspect, the present application provides a method for processing OCTA images, the method comprising: acquiring an OCTA image; performing a retinal area slice scan on the OCTA image to determine multiple frames of retinal slice images; calculating a decorrelation coefficient value for each frame of the retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; determining an adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image; for each frame of the retinal slice image, when it is determined that the decorrelation coefficient value of the current frame of the retinal slice image exceeds the adaptive threshold, performing three-dimensional filtering processing on the current frame of the retinal slice image to obtain a de-artifacted image corresponding to the OCTA image.

[0007] Furthermore, the above-mentioned step of calculating the decorrelation coefficient value of each frame of retinal slice image includes: taking each frame of retinal slice image as the current frame of retinal slice image, executing the following calculation steps: calculating the decorrelation coefficient corresponding to each pixel position in the current frame of retinal slice image; summing the decorrelation coefficients corresponding to multiple pixel positions respectively, to obtain the decorrelation coefficient value of the current frame of retinal slice image.

[0008] Furthermore, the step of calculating the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image includes: calculating the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image according to the following specified formula:

[0009]

[0010] Where D(i, j) represents the decorrelation coefficient of the current pixel position (i, j); A and B are two adjacent scan data corresponding to the current frame retinal slice image; B * It is the conjugate transpose of B, P and Q are the neighborhood sizes; u and v represent the ordinal numbers of the window scan.

[0011] Furthermore, the step of determining the adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image includes: calculating the mean of the decorrelation coefficients corresponding to all pixel positions for each frame of the retinal slice image to obtain a first coefficient mean corresponding to each frame of the retinal slice image; averaging the first coefficient means corresponding to multiple frames of retinal slice images again to obtain a second coefficient mean; and multiplying the second coefficient mean by an adjustable parameter to obtain an adaptive threshold.

[0012] Furthermore, the above adjustable parameter is 1.3.

[0013] Furthermore, the step of performing three-dimensional filtering on the current frame of retinal slice image includes: performing three-dimensional filtering on the current frame of retinal slice image according to the following formula:

[0014]

[0015] Wherein, filterframe represents the image after three-dimensional filtering, M, N, K are three-dimensional filtering window parameters; frame(i, j, k) represents the original data of the retinal slice image of the current frame.

[0016] Furthermore, when the above-mentioned determination that the decorrelation coefficient value of the current frame retinal slice image exceeds the adaptive threshold value further includes: determining that the current frame retinal slice image is a signal abnormality image.

[0017] In a second aspect, the present application also provides an OCTA image processing device, the device comprising: an image acquisition module, used to acquire OCTA images; a slice scanning module, used to perform retinal area slice scanning on the OCTA image to determine multiple frames of retinal slice images; a coefficient calculation module, used to calculate the decorrelation coefficient value of each frame of retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; a threshold determination module, used to determine an adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of retinal slice image; a three-dimensional filtering module, used to perform three-dimensional filtering processing on the current frame of retinal slice image for each frame of retinal slice image, when it is determined that the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold, to obtain a de-artifacted image corresponding to the OCTA image.

[0018] In a third aspect, the present application further provides an electronic device, comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method described in the first aspect above.

[0019] In a fourth aspect, the present application further provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method described in the first aspect above.

[0020] In a method, device and electronic device for processing OCTA images provided by the present application, an OCTA image is first acquired; then a retinal area slice scan is performed on the OCTA image to determine multiple frames of retinal slice images; then the decorrelation coefficient value of each frame of the retinal slice image is calculated; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; based on the decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image, an adaptive threshold is determined; for each frame of the retinal slice image, when it is determined that the decorrelation coefficient value of the current frame of the retinal slice image exceeds the adaptive threshold, the current frame of the retinal slice image is subjected to three-dimensional filtering processing to obtain a de-artifacted image corresponding to the OCTA image. In the present application, the three-dimensional decorrelation signal in the OCTA blood flow generation algorithm is used to determine the location where the white line artifact occurs, and then at the white line location, the white line noise is smoothed by three-dimensional filtering, which improves the white line artifacts without affecting the micro-blood vessels. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A flowchart of a method for processing OCTA images provided in an embodiment of the present application;

[0023] Figure 2 A schematic diagram of a normal decorrelation signal frame provided in an embodiment of the present application;

[0024] Figure 3 A schematic diagram of an abnormal decorrelation signal frame provided in an embodiment of the present application;

[0025] Figure 4 A comparison diagram of the effects of an OCTA image processing method provided in an embodiment of the present application;

[0026] Figure 5 A structural block diagram of an OCTA image processing device provided in an embodiment of the present application;

[0027] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The technical solution of the present application will be described clearly and completely below in conjunction with the embodiments. Obviously, the described embodiments are 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 the field without creative work are within the scope of protection of the present application.

[0029] There are two solutions for improving artifacts in the prior art:

[0030] Solution 1: Use complex hardware to track the motion of the sample to guide the OCT scan. Orthogonal scanning or Lissajous scanning mode can be used to correct motion artifacts. The main drawback is that these methods require additional equipment or improved scanning modes, which leads to increased costs.

[0031] Solution 2: Directly use image filtering algorithms to improve the artifact problem on OCTA enface images, including frequency domain notch filtering, tensor voting method, compensatory image filtering based on SVD decomposition, etc. The main drawback is that the image filtering method can improve the white line problem of motion artifacts, but the image details are easily deleted together with the stripes, resulting in the loss of information on the microvascular network.

[0032] Based on this, the embodiments of the present application provide an OCTA image processing method, device and electronic device, which utilize the three-dimensional decorrelation signal in the OCTA blood flow generation algorithm to determine the location where the white line artifact occurs, and then use three-dimensional filtering to smooth the white line noise at the white line position, thereby improving the white line artifact without affecting the tiny blood vessels.

[0033] To facilitate understanding of this embodiment, a method for processing OCTA images disclosed in an embodiment of the present application is first introduced in detail.

[0034] Figure 1 A flowchart of a method for processing an OCTA image provided in an embodiment of the present application, the method comprising the following steps:

[0035] Step S102, acquiring an OCTA image;

[0036] The above OCTA image is an optical coherence tomography angiography image to be processed.

[0037] Step S104, performing retinal area slice scanning on the OCTA image to determine multiple frames of retinal slice images;

[0038] When performing retinal area slice scanning on OCTA images, the retinal area is divided into 512 slice positions, that is, 512 frames of retinal slice images can be scanned;

[0039] Step S106, calculating the decorrelation coefficient value of each frame of the retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image;

[0040] The scanning at each slice position is usually performed multiple times, such as 2 or 4 times. The decorrelation coefficient is calculated between the multiple scanning data at the same slice position.

[0041] Step S108, determining an adaptive threshold based on decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image;

[0042] The decorrelation coefficients calculated from different data sequences are quite different. If a fixed threshold is used as the basis for judgment, many inappropriate situations will occur. Therefore, an adaptive threshold generation method is needed to dynamically generate the threshold based on the data features in each frame of the retinal slice image.

[0043] Step S110, for each frame of retinal slice image, when it is determined that the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold, three-dimensional filtering is performed on the current frame of retinal slice image to obtain a de-artifacted image corresponding to the OCTA image.

[0044] When the decorrelation coefficient value of the current frame retinal slice image exceeds the adaptive threshold, it can be determined that the current frame retinal slice image is a signal abnormality image, that is, an image including white line artifacts, and needs to be subjected to three-dimensional filtering processing.

[0045] The OCTA image processing method provided in the embodiment of the present application aims at the problem of white line artifacts in OCTA images and proposes a three-dimensional filtering method based on decorrelation signals, which can effectively remove white line artifacts while leaving small blood vessels unaffected.

[0046] The embodiment of the present application also provides another OCTA image processing method, which is implemented on the basis of the above embodiment; this embodiment focuses on describing the basic concept of the embodiment of the present application, the decorrelation coefficient value calculation process, the threshold determination process and the artifact removal process.

[0047] The OCTA blood flow generation algorithm calculates the correlation between the original complex data of multiple frames scanned at the same scanning position to determine the location of the blood flow. If there is an offset during the system acquisition process, the correlation of the calculated data becomes smaller and the decorrelation coefficient is large. On the contrary, the correlation of normal data is good and the decorrelation value is small. This constitutes the basis for determining the location of the white line artifact. Among them, the definition of the decorrelation coefficient is as follows:

[0048]

[0049] Where D represents the decorrelation coefficient of the current scanning position, A and B are the complex data of two adjacent frames, with a size of HxW, and D(i, j) represents the decorrelation coefficient of the subscript (i, j). The neighborhood data of (i, j) is required for calculation, and the range is (P, Q). Where B* is the conjugate transpose of B, i, j are the subscripts of the image pixels, and the range is [0, W-1] and [0, H-1]. P and Q are the neighborhood sizes. For a three-dimensional decorrelation matrix, it is composed of multiple decorrelation coefficients, and the decorrelation coefficient under the subscript of each pixel is expressed as D(i, j, k).

[0050] See also Figure 2 The normal decorrelated signal frame shown, and Figure 3 In the abnormal decorrelated signal frame shown, it can be seen that the retinal area is clearly distinguished from the background area. Figure 3 is abnormal data. The retinal area is very similar to the background. By using the difference between the decorrelation coefficients, the embodiment of the present application provides the following method for removing horizontal line artifacts.

[0051] First, the decorrelation coefficient of each frame of data is counted, and then the mean of the decorrelation coefficient of the entire sequence is calculated. Next, an adaptive threshold is set according to the mean to determine whether a frame in the sequence is an artifact frame. Finally, a three-dimensional filtering method is used to filter the white line noise at the location of the artifact frame, and the vascular image with the white line artifact removed is obtained after projection.

[0052] That is, the OCTA image processing method specifically includes the following steps:

[0053] Step 1: Acquire OCTA images; perform retinal area slice scanning on the OCTA images to determine multiple frames of retinal slice images;

[0054] Step 2: Calculate the decorrelation coefficient value of each frame of retinal slice image as above;

[0055] Specifically, each frame of retinal slice image is used as the current frame of retinal slice image, and the following calculation steps are performed:

[0056] Step 2.1: Calculate the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image; specifically, calculate the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image according to the following specified formula:

[0057]

[0058] Where D(i, j) represents the decorrelation coefficient of the current pixel position (i, j); A and B are two adjacent scan data corresponding to the current frame retinal slice image; B * It is the conjugate transpose of B, P and Q are the neighborhood sizes; u and v represent the ordinal numbers of the window scan.

[0059] Step 2.2: Sum the decorrelation coefficients corresponding to multiple pixel positions to obtain the decorrelation coefficient value of the current frame retinal slice image. The summation is performed as shown in the following formula:

[0060]

[0061] Where W and H are the sizes of the enveloping rectangle of the retinal area. k Indicates the decorrelation coefficient value of the current frame retinal slice image k; frame k (i, j) represents the decorrelation coefficient corresponding to the pixel position (i, j) in the current frame.

[0062] Step 3: Determine an adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image;

[0063] In a specific implementation, for each frame of retinal slice image, the mean of the decorrelation coefficients corresponding to all pixel positions is calculated to obtain the first coefficient mean corresponding to each frame of retinal slice image; the first coefficient means corresponding to multiple frames of retinal slice images are averaged again to obtain the second coefficient mean; the second coefficient mean is multiplied by an adjustable parameter to obtain an adaptive threshold.

[0064] Refer to the following formula to calculate the adaptive threshold thr:

[0065]

[0066] Among them, meanvalue represents the mean of the second coefficient; mean(framev k ) represents the first coefficient mean corresponding to the kth frame of retinal slice image; N represents the total number of frames; α is an adjustable parameter, and multiple frames of retinal slice images all use the same value, which is generally set to 1.3.

[0067] Step 4: for each frame of retinal slice image, determine whether the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold;

[0068] This step is actually to determine which image among multiple frames of retinal slice images has white line artifacts. If the decorrelation coefficient value framev>thr of a certain frame of retinal slice image, then the frame of retinal slice image is determined to be an abnormal signal image.

[0069] Step 5: When the adaptive threshold is exceeded, three-dimensional filtering is performed on the retinal slice image of the current frame;

[0070] Specifically, the retinal slice image of the current frame is subjected to three-dimensional filtering according to the following formula:

[0071]

[0072] Wherein, filterframe represents the image after three-dimensional filtering, M, N, K are three-dimensional filtering window parameters; frame(i, j, k) represents the original data of the retinal slice image of the current frame.

[0073] Figure 4 The effect of removing white line artifacts in the embodiment of the present application is shown. Figure (a) is the original image, and Figure (b) is the filtered image, and it can be seen that the white lines have been filtered out.

[0074] The OCTA image processing method provided in the embodiment of the present application proposes a three-dimensional filtering method based on decorrelation signals to address the white line artifact problem of OCTA images; that is, the three-dimensional decorrelation signals in the OCTA blood flow generation algorithm are used to determine the location where the white line artifact occurs, and then the white line noise is smoothed by three-dimensional filtering at the white line location, thereby improving the white line artifact without affecting the micro-blood vessels.

[0075] Based on the above method embodiment, the present application embodiment also provides an OCTA image processing device, see Figure 5 As shown, the device includes: an image acquisition module 502, used to acquire an OCTA image; a slice scanning module 504, used to perform retinal area slice scanning on the OCTA image to determine multiple frames of retinal slice images; a coefficient calculation module 506, used to calculate the decorrelation coefficient value of each frame of retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; a threshold determination module 508, used to determine an adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of retinal slice image; a three-dimensional filtering module 510, used to perform three-dimensional filtering processing on the current frame of retinal slice image when judging that the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold for each frame of retinal slice image, so as to obtain a de-artifacted image corresponding to the OCTA image.

[0076] Furthermore, the coefficient calculation module 506 is used to take each frame of retinal slice image as the current frame of retinal slice image, and perform the following calculation steps: calculate the decorrelation coefficient corresponding to each pixel position in the current frame of retinal slice image; sum the decorrelation coefficients corresponding to multiple pixel positions respectively, to obtain the decorrelation coefficient value of the current frame of retinal slice image.

[0077] Furthermore, the coefficient calculation module 506 is used to calculate the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image according to the following specified formula:

[0078]

[0079] Where D(i, j) represents the decorrelation coefficient of the current pixel position (i, j); A and B are two adjacent scan data corresponding to the current frame retinal slice image; B * It is the conjugate transpose of B, P and Q are the neighborhood sizes; u and v represent the ordinal numbers of the window scan.

[0080] Furthermore, the threshold determination module 508 is used to calculate the mean of the decorrelation coefficients corresponding to all pixel positions for each frame of retinal slice image, and obtain the first coefficient mean corresponding to each frame of retinal slice image; average the first coefficient means corresponding to multiple frames of retinal slice images again to obtain the second coefficient mean; and multiply the second coefficient mean by an adjustable parameter to obtain an adaptive threshold.

[0081] Furthermore, the above adjustable parameter is 1.3.

[0082] Furthermore, the three-dimensional filtering module 510 is used to perform three-dimensional filtering on the current frame retinal slice image according to the following formula:

[0083]

[0084] Wherein, filterframe represents the image after three-dimensional filtering, M, N, K are three-dimensional filtering window parameters; frame(i, j, k) represents the original data of the retinal slice image of the current frame.

[0085] Furthermore, the three-dimensional filtering module 510 is used to determine that the current frame of the retinal slice image is a signal abnormality image when the decorrelation coefficient value of the current frame of the retinal slice image exceeds an adaptive threshold.

[0086] The device provided in the embodiment of the present application has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the device, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0087] The present application also provides an electronic device, such as Figure 6 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device includes a processor 61 and a memory 60, the memory 60 stores computer executable instructions that can be executed by the processor 61, and the processor 61 executes the computer executable instructions to implement the above method.

[0088] exist Figure 6 In the illustrated embodiment, the electronic device further includes a bus 62 and a communication interface 63 , wherein the processor 61 , the communication interface 63 and the memory 60 are connected via the bus 62 .

[0089] Among them, the memory 60 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 63 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 62 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 62 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0090] The processor 61 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 61. The above processor 61 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor can be executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 61 reads the information in the memory and completes the steps of the method of the above embodiment in combination with its hardware.

[0091] An embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above method. The specific implementation can be found in the aforementioned method embodiment, which will not be repeated here.

[0092] The computer program products of the methods, devices, and electronic devices provided in the embodiments of the present application include a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0093] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0094] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0095] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0096] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for processing OCTA images, characterized in that: The method comprises: Acquire OCTA images; Performing retinal area slice scanning on the OCTA image to determine multiple frames of retinal slice images; Calculating the decorrelation coefficient value of each frame of the retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; Determine an adaptive threshold based on decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image; For each frame of retinal slice image, when it is determined that the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold, three-dimensional filtering is performed on the current frame of retinal slice image to obtain a de-artifacted image corresponding to the OCTA image.

2. The method according to claim 1, characterized in that The step of calculating the decorrelation coefficient value of each frame of retinal slice image includes: Take each frame of retinal slice image as the current frame of retinal slice image and perform the following calculation steps: Calculate the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image; sum the decorrelation coefficients corresponding to a plurality of pixel positions to obtain the decorrelation coefficient value of the current frame retinal slice image.

3. The method according to claim 2, characterized in that The step of calculating the decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image comprises: The decorrelation coefficient corresponding to each pixel position in the current frame retinal slice image is calculated according to the following specified formula: Where D(i, j) represents the decorrelation coefficient of the current pixel position (i, j); A and B are two adjacent scan data corresponding to the current frame retinal slice image; B * It is the conjugate transpose of B, P and Q are the neighborhood sizes; u and v represent the ordinal numbers of the window scan.

4. The method according to claim 1, characterized in that: The step of determining the adaptive threshold based on the decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image comprises: For each frame of retinal slice image, calculate the mean of decorrelation coefficients corresponding to all pixel positions respectively, and obtain the first coefficient mean corresponding to each frame of retinal slice image; The first coefficient means corresponding to the multiple frames of retinal slice images are averaged again to obtain a second coefficient mean; The adaptive threshold is obtained by multiplying the second coefficient mean by an adjustable parameter.

5. The method according to claim 4, characterized in that The adjustable parameter is 1.

3.

6. The method according to claim 1, characterized in that The step of performing three-dimensional filtering on the current frame retinal slice image comprises: According to the following formula, the retinal slice image of the current frame is subjected to three-dimensional filtering processing: Wherein, filterframe represents the image after three-dimensional filtering, M, N, K are three-dimensional filtering window parameters; frame(i, j, k) represents the original data of the current frame retinal slice image.

7. The method according to claim 1, characterized in that When it is determined that the decorrelation coefficient value of the current frame retinal slice image exceeds the adaptive threshold, the method further includes: determining that the current frame retinal slice image is a signal abnormality image.

8. An OCTA image processing device, characterized in that: The device comprises: An image acquisition module, used for acquiring OCTA images; A slice scanning module, used for performing a retinal area slice scan on the OCTA image to determine multiple frames of retinal slice images; A coefficient calculation module, used to calculate the decorrelation coefficient value of each frame of the retinal slice image; the decorrelation coefficient value is the sum of the decorrelation coefficients corresponding to all pixel positions in the retinal slice image; A threshold determination module, used for determining an adaptive threshold based on decorrelation coefficients corresponding to all pixel positions in each frame of the retinal slice image; The three-dimensional filtering module is used for performing three-dimensional filtering processing on the current frame of retinal slice image for each frame of retinal slice image when it is determined that the decorrelation coefficient value of the current frame of retinal slice image exceeds the adaptive threshold, so as to obtain a de-artifacted image corresponding to the OCTA image.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method according to any one of claims 1 to 7.

Images