Method and device for determining the smoothness of capillaries

Abstract

The present invention provides a method and device for determining the smoothness of the inner wall of a capillary. A segment of a capillary without bifurcations is determined according to an OCTA image. Scanning images of multiple scanning positions on the capillary without bifurcations are obtained, each scanning position corresponds to multiple scanning images, and the scanning images are arranged in time to obtain coded images of the light and dark changes of blood flow at each scanning position. Cross-correlation calculation of the coded images of two scanning positions corresponding to the scanning interval is performed to obtain the scanning interval cross-correlation coefficient, and the result of determining the smoothness of the inner wall of the capillary between the first scanning position and the second scanning position is obtained according to the corresponding relationship between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary. The present invention realizes the rapid determination of the smoothness of the capillary, and according to the difference in cross-correlation of different segments of the same capillary, the difference in smoothness of different positions of the same capillary can be further determined, thereby greatly improving the determination accuracy of the smoothness.

Description

Technical Field

[0001] The present invention relates to the technical field of optical coherence tomography, in particular to the technical field of retinal capillary detection, and in particular to a method for determining the smoothness of capillaries, a device for determining the smoothness of capillaries, a computer device, a computer-readable storage medium and a computer program product. Background Art

[0002] The statements in this section merely provide background art related to the present invention and do not necessarily constitute prior art.

[0003] Capillaries are the most widely distributed, thinnest-walled, and smallest-caliber blood vessels in the body. They can generally only accommodate red blood cells passing through in a single file. Their walls are mainly composed of a layer of endothelial cells, with a thin layer of connective tissue outside the endothelial cells. Because capillaries have thin walls and high permeability, oxygen and nutrients in the blood can enter the tissues through the walls, while carbon dioxide and metabolic products in the tissues can also enter the blood through the walls, thus completing the gas exchange and material exchange between blood and tissues. Experiments have shown that when endothelial cells are stimulated by certain chemicals or mechanical stimulation, they can contract to change the size of the tube diameter, and the smoother the inner wall of the capillaries, the smoother the blood flow, which is more conducive to material exchange.

[0004] However, studies have shown that when certain lesions occur in the human body, such as retinal arteriosclerosis, arterial thrombosis and hypertension, the smoothness of the inner walls of capillaries (such as retinal capillaries) may change. Most existing solutions use endoscopy to examine possible blockages or smoothness lesions in large blood vessels, and cannot accurately judge the smoothness of the inner walls of capillaries. Summary of the invention

[0005] In order to address the deficiencies in the prior art, the present invention provides a method and device for determining the smoothness of capillaries, which achieve rapid determination of the smoothness of capillaries in a non-invasive manner, and based on the differences in cross-correlations of blood flow OCTA encodings of different segments of the same capillary (each segment has the same length), further determine the differences in smoothness of different positions of the same capillary, thereby greatly improving the accuracy of smoothness determination; at the same time, pathological analysis can be performed based on the smoothness of multiple capillaries in a certain area.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a method for determining the smoothness of the inner wall of a capillary.

[0008] A method for determining the smoothness of the inner wall of a capillary comprises the following steps:

[0009] A segment of capillary without bifurcation was determined based on the acquired OCTA images;

[0010] Acquire scanned images of multiple scanned positions on the non-bifurcation capillary, each scanned position corresponds to multiple scanned images, arrange the scanned images in time, and obtain coded images of the light and dark changes of blood flow at each scanned position;

[0011] Taking the area between any two positions as the scanning interval, the cross-correlation calculation of the coded images of the two scanning positions corresponding to the scanning interval is performed to obtain the scanning interval cross-correlation coefficient, and the smoothness of the inner wall of the capillary is determined according to the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary.

[0012] As a further limitation of the first aspect of the present invention, the results of determining the smoothness of the inner wall of the capillary include at least two classifications: rough and smooth. When the correlation coefficient of any scanning interval is greater than the coefficient threshold, the inner wall of the capillary in this scanning interval is smooth; otherwise, the inner wall of the capillary in this scanning interval is rough.

[0013] As a further limitation of the first aspect of the present invention, for any two scanning intervals of the same length on a non-bifurcated capillary, the scanning interval with a larger correlation coefficient corresponds to a higher degree of smoothness; wherein the any two scanning intervals do not overlap.

[0014] As a further limitation of the first aspect of the present invention, for any two scanning intervals on a certain unbranched capillary, the scanning interval with a larger mutual correlation coefficient corresponds to a higher degree of smoothness; wherein, the any two scanning intervals are the Nth scanning interval and the N+1th scanning interval, and along the same scanning direction, the end scanning position of the Nth scanning interval and the beginning scanning position of the N+1th scanning interval are the same scanning position.

[0015] In a second aspect, the present invention provides a device for determining the smoothness of the inner wall of a capillary.

[0016] A device for determining the smoothness of the inner wall of a capillary, comprising:

[0017] An image acquisition unit is configured to: determine a segment of capillary blood vessels without bifurcations according to the acquired OCTA image;

[0018] The coded image acquisition unit is configured to: acquire scanned images of multiple scanned positions on the non-bifurcation capillary, each scanned position corresponds to multiple scanned images, and arrange the scanned images in time to obtain coded images of light and dark changes of blood flow at each scanned position;

[0019] The smoothness determination unit is configured to: take the area between any two positions as the scanning interval, perform cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtain the scanning interval cross-correlation coefficient, and obtain the smoothness determination result of the inner wall of the capillary in the scanning interval based on the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary.

[0020] As a further limitation of the second aspect of the present invention, in the smoothness determination unit, the capillary inner wall smoothness determination results include at least two classifications: rough and smooth. When the correlation coefficient of any scanning interval is greater than the coefficient threshold, the inner wall of the capillary in this scanning interval is smooth; otherwise, the inner wall of the capillary in this scanning interval is rough.

[0021] As a further limitation of the second aspect of the present invention, in the smoothness determination unit, for any two scanning intervals on a certain unbranched capillary, the scanning interval with a larger mutual correlation coefficient corresponds to a higher degree of smoothness; wherein the any two scanning intervals do not overlap, or the any two scanning intervals are the Nth scanning interval and the N+1th scanning interval, and along the same scanning direction, the end scanning position of the Nth scanning interval and the beginning scanning position of the N+1th scanning interval are the same scanning position.

[0022] In a third aspect, the present invention provides a computer device, comprising: a processor and a computer-readable storage medium;

[0023] a processor adapted to execute a computer program;

[0024] A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the method for determining the smoothness of the inner wall of a capillary as described in the first aspect of the present invention is implemented.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the method for determining the smoothness of the inner wall of a capillary as described in the first aspect of the present invention.

[0026] In a fifth aspect, the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the method for determining the smoothness of the inner wall of the capillary as described in the first aspect of the present invention.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] 1. The present invention innovatively proposes a method for determining the smoothness of the inner wall of capillaries, performs cross-correlation calculation of coded images of two scanning positions corresponding to a scanning interval, obtains a first cross-correlation coefficient, and obtains a result of determining the smoothness of the inner wall of capillaries in the first scanning interval based on the correspondence between the cross-correlation coefficient of the scanning interval and the smoothness of the inner wall of capillaries. The method uses a non-invasive approach to achieve rapid determination of the smoothness of capillaries.

[0029] 2. The present invention innovatively proposes a method for determining the smoothness of the inner wall of a capillary. For any two scanning intervals on a non-bifurcated capillary, the scanning interval with a larger correlation coefficient corresponds to a higher smoothness. Based on this, the difference in smoothness at different positions of the same capillary can be determined, greatly improving the accuracy and scope of application of smoothness determination.

[0030] Advantages of additional aspects of the present invention will be given in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0032] Figure 1 Schematic diagram of the smoothness of the same capillary at different scanning intervals provided in Example 1 of the present invention

[0033] Figure 2 A schematic diagram of a method for determining the smoothness of the inner wall of a capillary provided in Example 1 of the present invention;

[0034] Figure 3 A schematic diagram of a coded image provided by Embodiment 1 of the present invention;

[0035] Figure 4 A schematic diagram of an initial cross-sectional view provided in Example 1 of the present invention;

[0036] Figure 5 A schematic diagram of a capillary inner wall smoothness determination system provided in Example 2 of the present invention;

[0037] Figure 6 This is a schematic diagram of an electronic device provided in Example 3 of the present invention. DETAILED DESCRIPTION

[0038] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0039] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0040] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0041] Embodiment 1:

[0042] In this implementation, a method for determining the smoothness of the inner wall of a capillary is provided. The following is a brief introduction to the technical terms and related concepts involved in this processing scheme, including:

[0043] Capillaries are extremely tiny blood vessels that connect arteries and veins and are interconnected to form a network. They have thin walls, small diameters, and slow blood flow, and are used for the exchange of substances between blood and tissues. For example, the capillaries in the eye are generally distributed between the optic nerve layer and the inner nuclear layer of the retina. They are usually not visible to the naked eye and play an important role in eye health and function. Testing the blood flow velocity of the capillaries in the eye can effectively prevent or treat eye diseases. For example, retinal arteriosclerosis can lead to diffuse thinning of the retinal arteries, increased curvature, and thickening of the arterial walls. In severe cases, it can lead to blockage of fundus capillaries; when there is a thrombus in the arterial circulation, it may block the central retinal artery, leading to blockage of fundus capillaries; in patients with hypertension, it may cause spasm and blockage of fundus capillaries, leading to insufficient blood supply to the eyes, and the body's nutrients cannot be delivered to the eyes. The effects of long-term accumulation will lead to reduced vision or even loss of vision. Therefore, it is extremely important to measure the capillary blood flow velocity.

[0044] OCTA (Optical Coherence Tomography Angiography) is a new type of non-invasive fundus imaging technology that can identify retinal choroidal blood flow movement information with high resolution and image the retinal choroidal microvascular circulation in living tissue. It has unique advantages in the management and follow-up of normal retinal choroidal vascular changes and the detection of treatment effects.

[0045] The technical principle of OCTA is mainly based on one concept, that is, in a stationary eyeball (or subcutaneous tissue, using the eyeball as an example here), the only moving structure in the fundus is the blood cells flowing in the blood vessels. By repeatedly scanning the same cross-section and using special calculation methods (such as decorrelation of signal amplitude), a contrast between static and active structures is generated, thereby obtaining blood flow signals, and based on this, three-dimensional reconstruction of the vascular structure is performed.

[0046] The correlation coefficient is a statistical indicator first designed by statistician Karl Pearson. It is a measure of the linear correlation between variables. It is usually represented by the letter R. Due to the different research objects, there are many ways to define the correlation coefficient. The most commonly used one is the Pearson correlation coefficient. The absolute value of the R value is between 0 and 1. Generally speaking, the closer the absolute value of the R value is to 1, the stronger the correlation between the two quantities X and Y. Conversely, the closer the absolute value of the R value is to 0, the weaker the correlation between the two quantities X and Y.

[0047] Specifically, the method for determining the smoothness of the inner wall of a capillary provided by the present implementation is as follows: Figure 1 and Figure 2 As shown, the following process is included:

[0048] S1: A segment of capillary without bifurcation is determined based on the acquired OCTA images;

[0049] S2: Obtain scanned images of multiple scanned positions on the non-bifurcation capillary. Each scanned position corresponds to multiple scanned images. The scanned images are arranged in time to obtain coded images of the light and dark changes of the blood flow at each scanned position, such as Figure 3 As shown;

[0050] S3: Perform cross-correlation calculation of the encoded images of two scanning positions corresponding to the scanning interval to obtain a first cross-correlation coefficient, and obtain a capillary inner wall smoothness determination result of the first scanning interval based on the correspondence between the cross-correlation coefficient of the scanning interval and the smoothness of the capillary inner wall.

[0051] This implementation method is introduced by taking the identification of retinal capillaries as an example. Specifically, in S1, a segment of capillaries without bifurcations is determined, including:

[0052] Scan any two positions of a capillary region on the OCTA image (i.e., it can be roughly seen from the OCTA image that it may be a capillary), and each position corresponds to multiple initial cross-sectional images at different times, such as Figure 4 As shown, the cross-sectional images at each position are fused, and each position corresponds to a fused cross-sectional image;

[0053] A capillary signal on one fused cross-sectional image is selected and cross-correlated with all capillary signals on another fused cross-sectional image. When the cross-correlation coefficient is greater than or equal to the coefficient threshold, the capillaries between the two positions are judged to be the same capillary without bifurcation.

[0054] The cross-section diagrams at each location are fused, including:

[0055] For any position, 10 consecutive OCTA images at different times at this position are automatically selected for pixel averaging to reduce random noise and improve image quality. The pixel averaging here refers to adding the ten pixel values ​​of the same pixel point and taking the average value to obtain a fused image. It can be understood that there can be more OCTA images here, and the main purpose is to obtain more accurate capillary signals on the cross section.

[0056] The principle of capillary recognition in this implementation method is that we use the characteristic of red blood cells circulating in a single queue in the capillaries. The plasma and red blood cells scanned by the OCTA device will appear bright or dark respectively. The single flow of red blood cells in the capillaries will show a phenomenon of light and dark changes. By fusing multiple OCTA images at different times, we will definitely be able to find the brightness signals corresponding to all the capillaries. If only one image is used, the brightness signal may be missed, which will lead to the inability to identify the corresponding capillaries.

[0057] It can be understood that in some other implementations, the fusion processing here can also be performed by directly adding the pixel values ​​of the same pixel point, so that the area with brightness signals can always be found, and all blood vessel signals can be found in this way; or, further, the pixel values ​​of the same pixel point can be directly added to obtain all brightness signals, and then the brightness of all darker signals (i.e., tissue signals below a certain brightness threshold) is averaged, and the brightness signal greater than a certain brightness threshold is subtracted from the brightness average signal, and then the result is multiplied by a certain multiple to enhance the difference signal to obtain the final blood vessel signal. The above method is only for illustration, and other fusion methods can also be used to obtain the brightness signals corresponding to all blood vessels.

[0058] It is understandable that in some other implementations, the same unbranched capillary can also be determined by directly using a pre-trained image recognition algorithm to directly perform image recognition and extract an OCTA image of a section of unbranched capillary, which will not be elaborated here.

[0059] In this implementation, before determining the same unbranched capillary, a capillary signal recognition process is also included, specifically including:

[0060] The brightness on the fused cross-section image is contrasted. Blood vessels are those with brightness greater than the brightness threshold, and blood vessels are those with diameters less than the diameter threshold.

[0061] In this implementation, optionally, the brightness threshold may be determined in the following ways:

[0062] (1) According to the setting of empirical values, the general brightness value corresponding to the blood vessel can be obtained based on a large number of measurement results, and this general brightness value is used as the brightness threshold; (2) The maximum brightness and the minimum brightness on this fused cross-sectional image are obtained, and the average of the two is taken, and the average is taken as the brightness threshold; (3) All brightness signal values ​​on this fused cross-sectional image are obtained, all brightness signal values ​​are sorted, and the lowest brightness values ​​are removed (for example, 10%, of course, other values ​​can also be used, which are not specifically limited here and can be selected according to the situation), and the average of the remaining brightness values ​​is taken as the brightness threshold.

[0063] It is understandable that the brightness threshold may also be set in other ways, as long as it can effectively distinguish the brightness signal corresponding to the tissue (generally darker) from the brightness signal corresponding to the blood vessel (generally brighter), which will not be specifically illustrated here.

[0064] In this implementation, the diameter threshold may be determined in the following ways:

[0065] (1) According to the empirical value setting, the first diameter range corresponding to the large blood vessels and the second diameter range corresponding to the capillaries can be obtained based on a large number of measurement results. According to the minimum value of the first diameter range and the maximum value of the second diameter range, a value between the minimum value and the maximum value is determined as the diameter threshold; (2) The maximum blood vessel diameter value and the minimum blood vessel diameter value on this fused cross-sectional image are obtained, and the average of the two is taken as the blood vessel diameter threshold; (3) All blood vessel diameter values ​​on this fused cross-sectional image are obtained, all blood vessel diameter values ​​are sorted, the lowest 10% blood vessel diameter values ​​are removed, and the average of the remaining blood vessel diameter values ​​is taken as the diameter threshold.

[0066] It is understandable that the diameter threshold may also be set in other ways, such as large blood vessels and capillaries, which will not be specifically illustrated here.

[0067] Optionally, in some other implementations, the capillary signal recognition process may also be performed in the following manner:

[0068] For each point in the fused cross-sectional image, time is used as the horizontal axis, and the brightness signal of multiple repeated scans (for example, 10) is used as the vertical axis. The brightness signals at different times are compared. The area with a suitable size where the brightness signal is wavy and the fluctuation degree is greater than the threshold is the capillary signal, while the brightness of other tissues is in a relatively low and stable state, and the brightness of large blood vessels is in a relatively high and stable state.

[0069] In this implementation, the threshold of the mutual correlation coefficient is generally set according to an empirical value. For example, the coefficient threshold can be set to 0.2, that is, the mutual correlation coefficient greater than 0.2 is regarded as a capillary without bifurcation. Alternatively, the coefficient threshold can be set to 0.5 or other values, which will not be further described here.

[0070] In this implementation, in S2, a specific method for obtaining the encoded image is introduced with two scanning positions (i.e., the first position A1 and the second position A2), including:

[0071] Select a determined capillary without bifurcation in the OCTA image, designate a first position A1 and a second position A2 for the selected capillary, and perform alternating scanning;

[0072] It can be understood that the scanning of the first position A1 and the second position A2 does not necessarily have to be alternating scanning, but can also be intermittent scanning. When performing scanning work at multiple positions, the scanning process can be configured according to needs. By using alternating scanning, intermittent scanning or other scanning methods, corresponding multiple scanning images can be obtained for subsequent analysis.

[0073] Extract multiple scan images (i.e., first scan images) at different times of the first position A1, arrange the multiple first scan images according to time, and mark the capillary positions; extract multiple scan images (i.e., second scan images) at different times of the second position A2, arrange the multiple second scan images according to time, and mark the capillary positions;

[0074] The capillary region at the same position marked by the first position A1 is extracted and arranged according to time to obtain a coded image of the light and dark changes of the capillary blood flow at the first position A1, that is, a first coded image; the capillary region at the same position marked by the second position A2 is extracted and arranged according to time to obtain a coded image of the light and dark changes of the capillary blood flow at the second position A2, that is, a second coded image, as shown in FIG. Figure 2 shown.

[0075] It can be understood that when there are multiple scanning positions, such as the third position A3, the fourth scanning position A4, etc., the encoded images of each position, such as the third encoded image and the fourth encoded image, can be obtained in sequence in the above manner. It can be selected according to specific needs and will not be elaborated here.

[0076] In this implementation, in S3, specifically, the capillary inner wall smoothness determination result includes at least two classifications: rough and smooth. When the scanning interval correlation coefficient is greater than the coefficient threshold, the capillary inner wall is smooth, otherwise, the capillary inner wall is rough.

[0077] It can be understood that the smoothness of capillaries is positively correlated with the mutual correlation coefficient, that is, the larger the mutual correlation coefficient between two scans, the smoother the capillary segment between the two scanning positions. Therefore, more levels of smoothness can be set, such as particularly smooth, smooth, general, rough and particularly rough, etc. Of course, other subdivision methods can also be used, which will not be repeated here.

[0078] In this implementation, optionally, a cross-correlation calculation is performed on the coded images of the third scanning position and the fourth scanning position to obtain a second scanning interval cross-correlation coefficient, and when the first scanning interval cross-correlation coefficient is smaller than the second scanning interval cross-correlation coefficient, it is determined that the roughness of the inner wall of the capillary in the first scanning interval is greater than the roughness of the inner wall in the second scanning interval;

[0079] On the contrary, it is determined that the inner wall roughness in the first scanning interval is less than or equal to the inner wall roughness in the second scanning interval.

[0080] Understandable, such as Figure 1 As shown, by comparison, it can also be concluded that the smoothness of the Nth scanning interval is greater than the smoothness of the first scanning interval. The mutual correlation coefficients of each scanning interval can be compared, which will not be repeated here.

[0081] It can be understood that by continuously selecting scanning positions, a finer division of the smoothness of a certain unbranched capillary can be achieved, thereby determining the segment of the tube that may be at risk of congestion and improving the quality of medical diagnosis or treatment.

[0082] In this implementation, when the third scanning position coincides with the second scanning position, the capillary segment between the first scanning position and the second scanning position coincides with the capillary segment between the third scanning position and the fourth scanning position at the intersection; when the third scanning position and the second scanning position are located at different positions of the same unbranched capillary, the capillary segment between the first scanning position and the second scanning position coincides with the capillary segment between the third scanning position and the fourth scanning position.

[0083] Embodiment 2:

[0084] like Figure 5 As shown, this implementation provides a device for determining the smoothness of the inner wall of a capillary, comprising:

[0085] An image acquisition unit is configured to: determine a segment of capillary blood vessels without bifurcations according to the acquired OCTA image; the specific working method of this unit is the same as the process of step S1 in embodiment 1, and will not be repeated here;

[0086] The coded image acquisition unit is configured to: acquire scanned images of multiple scanned positions on the non-bifurcation capillary, each scanned position corresponds to multiple scanned images, and arrange the scanned images in time to obtain a coded image of the light and dark changes of the blood flow at each scanned position; the specific working method of this unit is the same as the process of step S2 in embodiment 1, and will not be repeated here;

[0087] The smoothness determination unit is configured to: take the area between any two positions as the scanning interval, perform cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtain the scanning interval cross-correlation coefficient, and obtain the smoothness determination result of the inner wall of the capillary in the scanning interval according to the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary; the specific working method of this unit is the same as the process of step S3 in Example 1, which will not be repeated here.

[0088] It is understandable that the above-mentioned units can be separately or all combined into one or several other units to constitute, or some of the units can be further divided into multiple smaller units in function to constitute, which can achieve the same operation without affecting the realization of the technical effects of the embodiments of the present application. The above-mentioned units are divided based on logical functions. In practical applications, the function of one unit can also be implemented by multiple units, or the functions of multiple units can be implemented by one unit. In other embodiments of the present application, the image processing device may also include other units. In practical applications, these functions can also be implemented with the assistance of other units, and can be implemented by the collaboration of multiple units.

[0089] According to another embodiment of the present application, the system described in this embodiment can be constructed, and the control processing method of the embodiment of the present application can be implemented by running a computer program (including program code) capable of executing the steps involved in the corresponding method described in Example 1 on a general computing device such as a computer including processing elements and storage elements such as a central processing unit (CPU), random access memory (RAM), and read-only memory (ROM). The computer program can be recorded on, for example, a computer-readable recording medium, and loaded into the above-mentioned computing device through the computer-readable recording medium and run therein.

[0090] Embodiment 3:

[0091] like Figure 6As shown, this implementation provides an electronic device, which includes a processor 1001, a communication interface 1002, and a computer-readable storage medium 1003. The processor 1001, the communication interface 1002, and the computer-readable storage medium 1003 may be connected via a bus or other means.

[0092] Among them, the communication interface 1002 is used to receive and send data, the computer-readable storage medium 1003 can be stored in the memory of the electronic device, the computer-readable storage medium 1003 is used to store a computer program, the computer program includes program instructions, and the processor 1001 is used to execute the program instructions stored in the computer-readable storage medium 1003.

[0093] The processor 1001 (or CPU (Central Processing Unit)) is the computing core and control core of the electronic device, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the following process:

[0094] Determine a segment of capillary without bifurcation according to the acquired OCTA image; the specific working method of this unit is the same as the process of step S1 in embodiment 1, which will not be repeated here;

[0095] The scanning images of multiple scanning positions on the non-bifurcation capillary are obtained, each scanning position corresponds to multiple scanning images, and the scanning images are arranged in time to obtain a coded image of the light and dark changes of the blood flow at each scanning position; the specific working method of this unit is the same as the process of step S2 in embodiment 1, and will not be repeated here;

[0096] Taking the area between any two positions as the scanning interval, performing cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtaining the scanning interval cross-correlation coefficient, and obtaining the result of the smoothness of the inner wall of the capillary in the scanning interval according to the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary; the specific working method of this unit is the same as the process of step S3 in Example 1, which will not be repeated here.

[0097] Embodiment 4:

[0098] This implementation provides a computer-readable storage medium (Memory), which is a memory device in an electronic device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in the electronic device and, of course, extended storage media supported by the electronic device. The computer-readable storage medium provides a storage space that stores the processing system of the electronic device.

[0099] In addition, the storage space also stores one or more instructions suitable for being loaded and executed by the processor, and these instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM memory, or a non-volatile memory (non-volatile memory), such as at least one disk storage; optionally, it may also be at least one computer-readable storage medium located away from the aforementioned processor.

[0100] In one embodiment, the computer-readable storage medium stores one or more instructions; the processor loads and executes the one or more instructions stored in the computer-readable storage medium to implement the following steps:

[0101] Determine a segment of capillary without bifurcation according to the acquired OCTA image; the specific working method of this unit is the same as the process of step S1 in embodiment 1, which will not be repeated here;

[0102] The scanning images of multiple scanning positions on the non-bifurcation capillary are obtained, each scanning position corresponds to multiple scanning images, and the scanning images are arranged in time to obtain a coded image of the light and dark changes of the blood flow at each scanning position; the specific working method of this unit is the same as the process of step S2 in embodiment 1, and will not be repeated here;

[0103] Taking the area between any two positions as the scanning interval, performing cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtaining the scanning interval cross-correlation coefficient, and obtaining the result of the smoothness of the inner wall of the capillary in the scanning interval according to the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary; the specific working method of this unit is the same as the process of step S3 in Example 1, which will not be repeated here.

[0104] Embodiment 5:

[0105] This implementation provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device performs the following steps:

[0106] Determine a segment of capillary without bifurcation according to the acquired OCTA image; the specific working method of this unit is the same as the process of step S1 in embodiment 1, which will not be repeated here;

[0107] The scanning images of multiple scanning positions on the non-bifurcation capillary are obtained, each scanning position corresponds to multiple scanning images, and the scanning images are arranged in time to obtain a coded image of the light and dark changes of the blood flow at each scanning position; the specific working method of this unit is the same as the process of step S2 in embodiment 1, and will not be repeated here;

[0108] Taking the area between any two positions as the scanning interval, performing cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtaining the scanning interval cross-correlation coefficient, and obtaining the result of the smoothness of the inner wall of the capillary in the scanning interval according to the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary; the specific working method of this unit is the same as the process of step S3 in Example 1, which will not be repeated here.

[0109] A person skilled in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0110] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing computer program instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instruction can be stored in a computer-readable storage medium or transmitted by a computer-readable storage medium. The computer instruction can be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (for example, coaxial cable, optical fiber, digital line (DSL)) or wireless (for example, infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server, a data center, etc. that contains one or more available media integration. Available media can be magnetic media (for example, floppy disk, hard disk, tape), optical media (for example, DVD), or semiconductor media (for example, solid-state drive (Solid State Disk, SSD)) and the like.

[0111] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for determining the smoothness of the inner wall of a capillary, characterized in that: The process includes: A segment of capillary without bifurcation was determined based on the acquired OCTA images; Acquire scanned images of multiple scanned positions on the non-bifurcation capillary, each scanned position corresponds to multiple scanned images, arrange the scanned images in time, and obtain coded images of the light and dark changes of blood flow at each scanned position; Taking the area between any two positions as the scanning interval, performing cross-correlation calculation of the coded images of the two scanning positions corresponding to the scanning interval, obtaining the scanning interval cross-correlation coefficient, and obtaining the result of the determination of the smoothness of the inner wall of the capillary in the scanning interval according to the corresponding relationship between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary; The smoothness of the capillary is positively correlated with the mutual correlation coefficient; for any two scanning intervals on a non-bifurcated capillary, the scanning interval with a larger mutual correlation coefficient corresponds to a higher smoothness; wherein the any two scanning intervals do not overlap.

2. The method for determining the smoothness of the inner wall of a capillary according to claim 1, characterized in that: The capillary inner wall smoothness determination result includes at least two classifications: rough and smooth. When the correlation coefficient of any scanning interval is greater than the coefficient threshold, the inner wall of the capillary in this scanning interval is smooth. Otherwise, the inner wall of the capillary in this scanning interval is rough.

3. The method for determining the smoothness of the inner wall of a capillary according to claim 1, characterized in that: For any two scanning intervals of the same length on a certain unbranched capillary, the scanning interval with a larger mutual correlation coefficient corresponds to a higher degree of smoothness; wherein the any two scanning intervals are the Nth scanning interval and the N+1th scanning interval, and along the same scanning direction, the end scanning position of the Nth scanning interval and the beginning scanning position of the N+1th scanning interval are the same scanning position.

4. A device for determining the smoothness of the inner wall of a capillary, characterized in that: include: An image acquisition unit is configured to: determine a segment of capillary blood vessels without bifurcations according to the acquired OCTA image; The coded image acquisition unit is configured to: acquire scanned images of multiple scanned positions on the non-bifurcation capillary, each scanned position corresponds to multiple scanned images, and arrange the scanned images in time to obtain coded images of light and dark changes of blood flow at each scanned position; The smoothness determination unit is configured to: take the area between any two positions as the scanning interval, perform cross-correlation calculation of the encoded images of the two scanning positions corresponding to the scanning interval, obtain the scanning interval cross-correlation coefficient, and obtain the smoothness determination result of the inner wall of the capillary in the scanning interval based on the correspondence between the scanning interval cross-correlation coefficient and the smoothness of the inner wall of the capillary.

5. The device for determining the smoothness of the inner wall of a capillary according to claim 4, characterized in that: In the smoothness determination unit, the capillary inner wall smoothness determination result includes at least two categories: rough and smooth. When the correlation coefficient of any scanning interval is greater than the coefficient threshold, the inner wall of the capillary in this scanning interval is smooth, otherwise the inner wall of the capillary in this scanning interval is rough.

6. The device for determining the smoothness of the inner wall of a capillary according to claim 4, characterized in that: In the smoothness determination unit, for any two scanning intervals on a certain unbranched capillary, the scanning interval with a larger mutual correlation coefficient corresponds to a higher smoothness; wherein the any two scanning intervals do not overlap, or the any two scanning intervals are the Nth scanning interval and the N+1th scanning interval, and along the same scanning direction, the end scanning position of the Nth scanning interval and the beginning scanning position of the N+1th scanning interval are the same scanning position.

7. A computer device, characterized in that: include: A processor and a computer readable storage medium; a processor adapted to execute a computer program; A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, the method for determining the smoothness of the inner wall of a capillary as described in any one of claims 1 to 3 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing the method for determining the smoothness of the inner wall of a capillary as described in any one of claims 1-3.

9. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the method for determining the smoothness of the inner wall of a capillary as described in any one of claims 1 to 3 is implemented.

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