Image-based blood flow velocity measurement method, system, device, product and medium

Abstract

The invention relates to the technical field of image processing, and provides an image-based blood flow velocity measurement method, system and device, a product and a medium, and the method comprises the steps: selecting a to-be-measured capillary; selecting a first position and a second position on the capillary to be measured, and measuring a horizontal azimuth difference and a vertical azimuth difference; respectively obtaining a first red blood cell image number and a second red blood cell image number, and calculating a red blood cell interval difference according to the first red blood cell image number and the second red blood cell image number; constructing a first motion equation and a second motion equation, and resolving through the first motion equation and the second motion equation to obtain a red blood cell velocity relationship; and constructing a differential relational expression of the red blood cell acceleration, substituting the red blood cell velocity relation and the second motion equation into the differential relational expression to obtain a target differential equation, and resolving the target differential equation to obtain the blood flow velocity. The blood flow velocity can be conveniently measured.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly to an image-based blood flow velocity measurement method, system, device, product and medium. Background Art

[0002] In the fields of biomedical research and clinical diagnosis, accurately measuring blood flow velocity is crucial for understanding the physiological and pathological states of the human body. Especially in the measurement of retinal capillary blood flow, the results are of great significance for the early diagnosis, condition monitoring and treatment plan formulation of various diseases. Currently, a variety of technologies have been applied to blood flow velocity measurement, but they each have certain limitations.

[0003] Laser Doppler flowmetry, pulsed optical laser Doppler imaging technology, and optical Doppler tomography can measure blood flow velocity by utilizing the Doppler effect caused by blood flow. These methods have high accuracy in real-time blood flow velocity detection, but they have relatively strict requirements for the measurement environment and are highly sensitive to the angle between blood flow and the light beam, which limits their wide application in some scenarios.

[0004] Fluorescein fundus angiography is mainly used for observing blood vessel morphology. Although it can also analyze blood flow velocity and time information by combining specific software, especially in the examination of fundus microvessels, this method requires injection of fluorescein, which has certain risks such as allergic reactions, and the measurement process is relatively cumbersome.

[0005] Near-infrared spectroscopy analyzes blood flow velocity and blood oxygen content. Although it cannot directly measure blood flow velocity, it can provide valuable information for hemodynamics and is widely used in experimental research. However, the accuracy of its measurement results is affected by various factors such as differences in tissue optical properties.

[0006] In addition, Chinese Patent with publication number CN117752298A discloses a capillary blood flow velocity measurement method and system based on OCTA. By using the different absorption of spectra by different tissues, plasma and red blood cells, capillaries are selected for scanning imaging on non-invasive retinal OCTA images, the absorption spectra are obtained and processed, and the blood flow velocity and direction are measured by evaluating the similarity of the spectral absorption curves. This method solves some measurement problems to a certain extent, but there are still limitations. For example, the dependence on spectral analysis makes the measurement process relatively complex and requires high professional requirements for equipment and operators. Summary of the Invention

[0007] The present invention aims to solve at least one of the technical problems existing in the related art. To this end, the present invention provides an image-based blood flow velocity measurement method to reduce the limitations of the measurement environment and the angle between blood flow and the light beam, reduce the operation difficulty, without injecting fluorescein, calculate the flow velocity through image acquisition and processing and a mathematical model, improve the measurement accuracy and stability, and achieve the measurement of capillary blood flow velocity with a wide range of applications.

[0008] The present invention provides an image-based blood flow velocity measurement method, including: S1: Deploy an OCTA device, select a target measurement area through the OCTA device, and select a capillary to be measured in the target measurement area through the OCTA device; S2: Scan the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured, select a first position and a second position in the image of the capillary to be measured, and obtain a horizontal azimuth difference and a vertical azimuth difference; S3: The OCTA device performs image acquisition on the first position and the second position to respectively obtain a first number of red blood cell images and a second number of red blood cell images, and calculate a red blood cell interval difference through the first number of red blood cell images and the second number of red blood cell images; S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration, construct a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, construct a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, and solve the first motion equation and the second motion equation to obtain a red blood cell velocity relationship; S5: Construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relationship and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0009] According to the image-based blood flow velocity measurement method provided by the present invention, step S1 further includes: S11: Deploy the OCTA device, determine a sample to be measured, select a target measurement area on the sample to be measured through the OCTA device, determine the blood vessel distribution condition and observation conditions of the target measurement area, and determine candidate capillaries according to the blood vessel distribution condition and the observation conditions; S12: Observe the candidate capillaries through the OCTA device, and select the capillary to be measured from the candidate capillaries.

[0010] According to the image-based blood flow velocity measurement method provided by the present invention, step S2 further includes: S21: Scan the capillary to be measured through the OCTA device to obtain an initial capillary image to be measured. Denoise and remove artifacts from the initial capillary image to be measured to obtain a capillary image to be measured. Select both ends of a straight capillary in the capillary image to be measured as the first position and the second position; S22: Select a first measurement point at the first position and a second measurement point at the second position. The OCTA device measures the capillary to be measured between the first measurement point and the second measurement point to obtain the horizontal azimuth difference and the vertical azimuth difference.

[0011] According to the image-based blood flow velocity measurement method provided by the present invention, step S3 further includes: S31: Determine the sampling time. According to the sampling time, perform image acquisition with equal duration on the first position and the second position to obtain a first position image set and a second position image set respectively; S32: Obtain the red blood cell brightness in the first position image set and the second position image set, determine the brightness threshold, and count the number of images in the first position image set where the red blood cell brightness exceeds the brightness threshold to obtain the first red blood cell image number. Count the number of images in the second position image set where the red blood cell brightness exceeds the brightness threshold to obtain the second red blood cell image number; S33: Count the sizes of red blood cells in the first position image set and the second position image set to obtain the average red blood cell length. Calculate the red blood cell interval difference between the first position and the second position through the average red blood cell length, the first red blood cell image number, and the second red blood cell image number.

[0012] According to the image-based blood flow velocity measurement method provided by the present invention, in step S4, the expression of the first motion equation is: Where is the red blood cell acceleration, is the red blood cell interval difference, is the relative second red blood cell velocity, is the relative first red blood cell velocity. The reference velocity of the relative first red blood cell velocity and the relative second red blood cell velocity is the first red blood cell velocity, so = 0, ; The expression of the second motion equation is: Where is the horizontal azimuth difference, is the second red blood cell velocity, is the first red blood cell velocity, and the reference velocities of the first red blood cell velocity and the second red blood cell velocity are 0; The expression of the red blood cell velocity relationship is: .

[0013] According to the image-based blood flow velocity measurement method provided by the present invention, in step S2, the OCTA device obtains the horizontal azimuth difference and the vertical azimuth difference between the first position and the second position by the pixel coordinate method.

[0014] According to the image-based blood flow velocity measurement method provided by the present invention, in step S31, during the process of image acquisition, the time interval between two image acquisitions is not less than the minimum time interval.

[0015] According to the image-based blood flow velocity measurement method provided by the present invention, in step S32, the number of images in the first position image set in which the brightness of red blood cells exceeds the brightness threshold is counted, and the number of first red blood cell images is obtained through the scattering intensity threshold and the signal-to-noise ratio threshold. The number of images in the second position image set in which the brightness of red blood cells exceeds the brightness threshold is counted, and the number of second red blood cell images is obtained through the scattering intensity threshold and the signal-to-noise ratio threshold.

[0016] The present invention also provides an image-based blood flow velocity measurement system, including: A to-be-measured capillary selection module: used to deploy the OCTA device, select a target measurement area through the OCTA device, and select a to-be-measured capillary in the target measurement area through the OCTA device; An azimuth difference measurement module: used to scan the to-be-measured capillary through the OCTA device to obtain an image of the to-be-measured capillary, select a first position and a second position in the image of the to-be-measured capillary, and obtain the horizontal azimuth difference and the vertical azimuth difference; An image acquisition module: used to perform image acquisition on the first position and the second position by the OCTA device, respectively obtain the number of first red blood cell images and the number of second red blood cell images, and calculate the red blood cell interval difference through the number of first red blood cell images and the number of second red blood cell images; A velocity relationship calculation module: used to construct the first red blood cell velocity, the second red blood cell velocity and the red blood cell acceleration, construct a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, construct a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, and calculate the red blood cell velocity relationship through the first motion equation and the second motion equation; Blood flow velocity calculation module: used to construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relation and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0017] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the image-based blood flow velocity measurement method as described in any one of the above are implemented.

[0018] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the image-based blood flow velocity measurement method as described in any one of the above are implemented.

[0019] The present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the steps of the image-based blood flow velocity measurement method as described in any one of the above.

[0020] One or more of the above technical solutions in the embodiments of the present invention have at least one of the following technical effects: The image-based blood flow velocity measurement method, system, device, product, and medium provided by the present invention use an OCTA device to collect images and measure the blood flow velocity through the red blood cell interval difference. It does not need to continuously track individual red blood cells, so there is no need to acquire images at a high sampling rate, thereby effectively reducing the requirements for equipment and acquisition rate, and also reducing the probability of measurement failure or measurement error.

[0021] In addition, the method used in the present invention does not involve the acquisition of phase difference, thereby effectively expanding the acquisition range applicable to the present invention. It can adapt to more types of capillaries. Only the position relationship needs to be calculated through the pixel information of the image to calculate the blood flow velocity. Therefore, it has stronger adaptability and improves the adaptability of the present invention to different environments.

[0022] The additional aspects and advantages of the present invention will be partially given in the following description, partially become apparent from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0023] To more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0024] Figure 1 It is a schematic flowchart of the method for measuring blood flow velocity based on images provided by the present invention.

[0025] Figure 2 It is a schematic diagram of the first position and the second position of the method for measuring blood flow velocity based on images provided by the present invention; Figure 3 It is a schematic diagram of the situation where red blood cells exist at the first position in the first position image set of the method for measuring blood flow velocity based on images provided by the present invention; Figure 4 It is a schematic diagram of the situation where no red blood cells exist at the first position in the first position image set of the method for measuring blood flow velocity based on images provided by the present invention; Figure 5 It is a schematic structural diagram of the system for measuring blood flow velocity based on images provided by the present invention.

[0026] Figure 6 It is a schematic structural diagram of the device for measuring blood flow velocity based on images provided by the present invention.

[0027] Reference numerals: 1. First position; 2. Second position; 100. Module for selecting the capillary to be measured; 200. Azimuth difference measurement module; 300. Image acquisition module; 400. Speed relationship calculation module; 500. Blood flow velocity calculation module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed implementation manners

[0028] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope protected by the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0029] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0030] In the description of the embodiments of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "connected" and "coupled" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific situations.

[0031] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0032] The following Figures 1 to 6 describes the implementation scheme of the present invention: Figure 1 is a schematic flow chart of a method for measuring blood flow velocity based on images. First, a target measurement area is selected, and then the capillaries to be measured are selected through an OCTA device; then a first position and a second position are selected, and the horizontal azimuth difference and the vertical azimuth difference are obtained; subsequently, image acquisition is performed, and the erythrocyte interval difference is calculated; then a first motion equation and a second motion equation are constructed to obtain the erythrocyte velocity relationship; finally, the target differential equation is obtained and solved to obtain the blood flow velocity.

[0033] S1: Arrange the OCTA device, select the target measurement area through the OCTA device, and select the capillaries to be measured through the OCTA device in the target measurement area; Furthermore, the purpose of this stage is to determine the target measurement area, and then obtain the image of the target measurement area through the OCTA device to determine the capillaries to be measured. Step S1 specifically includes: S11: Arrange the OCTA device, determine the sample to be measured, select the target measurement area through the OCTA device on the sample to be measured, determine the blood vessel distribution status and observation conditions of the target measurement area, and determine the candidate capillaries according to the blood vessel distribution status and the observation conditions; S12: Observe the candidate capillaries through the OCTA device, and select the capillaries to be measured from the candidate capillaries.

[0034] For the above steps, the specific implementation in this embodiment is as follows: First, deploy the OCTA device, determine the object to be observed by the OCTA device, and use the object to be observed by the OCTA device as the sample to be measured. Since the OCTA device has certain requirements for the permeability of the observed area on biological tissues, the vascular distribution, etc., too complex capillary distribution may interfere with the observation of the OCTA device. And when the purpose of measuring blood flow velocity is to assist in disease diagnosis, it is also necessary to observe the capillaries in potential lesion sites. Therefore, it is first necessary to observe through the OCTA device to select a potential lesion area with relatively simple vascular distribution and meeting the observation conditions of the OCTA device on the sample to be measured as the target measurement area of the OCTA device. In the target measurement area, initially select several relatively straight, smooth capillaries without obvious breakage and thrombus as candidate capillaries.

[0035] Then, observe the candidate capillaries through the OCTA device, observe and evaluate the straightness, vascular integrity, permeability, etc. of the candidate capillaries, and select the capillary with the highest straightness, the best vascular integrity and permeability as the capillary to be measured.

[0036] S2: Scan the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured. Select a first position and a second position in the image of the capillary to be measured, and obtain the horizontal azimuth difference and the vertical azimuth difference; Furthermore, the purpose of this stage is to select the first position and the second position, calculate the horizontal azimuth difference and the vertical azimuth difference between the first position and the second position, so as to provide data for the subsequent blood flow velocity measurement process. Step S2 specifically includes: S21: Scan the capillary to be measured through the OCTA device to obtain an initial image of the capillary to be measured. Denoise and remove artifacts from the initial image of the capillary to be measured to obtain an image of the capillary to be measured. Select both ends of a straight capillary in the image of the capillary to be measured as the first position and the second position; S22: Select a first measurement point at the first position and a second measurement point at the second position. The OCTA device measures the capillary to be measured between the first measurement point and the second measurement point to obtain the horizontal azimuth difference and the vertical azimuth difference.

[0037] In addition, in step S2, the OCTA device obtains the horizontal azimuth difference and the vertical azimuth difference between the first position and the second position through the pixel coordinate method.

[0038] For the above steps, the specific implementation in this embodiment is as follows: First, use an OCTA device to scan the capillary to be measured to obtain an initial image of the capillary to be measured, and perform noise reduction and artifact removal on the image. Here, the orientation of the capillary to be measured in the image of the capillary to be measured is a horizontal orientation. Select both ends of a relatively straight section of the capillary on the image of the capillary to be measured as the first position and the second position. In this embodiment, the blood flows from the first position to the second position. The selection of the first position and the second position can be done manually or automatically by a computer to select more appropriate first and second positions. The first position and the second position of the capillary to be measured are as Figure 2 shown.

[0039] Subsequently, select a first measurement point at the first position and a second measurement point at the second position. In this embodiment, the first measurement point is the center point of the blood vessel of the capillary to be measured at the first position, and the second measurement point is the center point of the blood vessel of the capillary to be measured at the second position. Subsequently, the OCTA device measures the horizontal azimuth difference and the vertical azimuth difference between the first position and the second position by the pixel coordinate method.

[0040] The pixel coordinate method means that the OCTA device establishes a rectangular coordinate system in the image it scans. In this embodiment, the origin of the rectangular coordinate system is the lower left corner of the image, with the horizontal direction as the x-axis and the vertical direction as the y-axis. Then the OCTA device obtains the actual size of the area where the scanned image is located, the pixels of the image, and the magnification of the image. Combining the actual size of the area where the image is located, the pixels of the image, and the magnification of the image can obtain the length represented by a pixel point in the image. Subsequently, the OCTA device calculates the number of pixels of the projection of the capillary to be measured between the first measurement point and the second measurement point on the x-axis, and multiplies the number of pixels by the length represented by a pixel point to obtain the horizontal azimuth difference; the OCTA device calculates the number of pixels of the projection of the capillary to be measured between the first measurement point and the second measurement point on the y-axis, and multiplies the number of pixels by the length represented by a pixel point to obtain the vertical azimuth difference.

[0041] S3: The OCTA device performs image acquisition on the first position and the second position to obtain a first red blood cell image quantity and a second red blood cell image quantity respectively, and calculates the red blood cell interval difference through the first red blood cell image quantity and the second red blood cell image quantity; Furthermore, the purpose of this stage is to perform image acquisition on the first position and the second position to obtain a first red blood cell image quantity and a second red blood cell image quantity, and then calculate the red blood cell interval difference for use in subsequent calculations. Step S3 specifically includes: S31: Determine the sampling time, and perform image acquisition of equal duration on the first position and the second position according to the sampling time, respectively obtaining a first-position image set and a second-position image set; S32: Obtain the brightness of red blood cells in the first-position image set and the second-position image set, determine a brightness threshold, and count the number of images in the first-position image set where the brightness of red blood cells exceeds the brightness threshold to obtain a first red blood cell image count, and count the number of images in the second-position image set where the brightness of red blood cells exceeds the brightness threshold to obtain a second red blood cell image count; S33: Count the sizes of red blood cells in the first-position image set and the second-position image set to obtain an average red blood cell length, and calculate the red blood cell interval difference between the first position and the second position based on the average red blood cell length, the first red blood cell image count, and the second red blood cell image count.

[0042] In step S31, during the process of image acquisition, the time interval between two image acquisitions is not less than the minimum time interval.

[0043] In step S32, count the number of images in the first-position image set where the brightness of red blood cells exceeds the brightness threshold, and obtain the first red blood cell image count through a scattering intensity threshold and a signal-to-noise ratio threshold. Count the number of images in the second-position image set where the brightness of red blood cells exceeds the brightness threshold, and obtain the second red blood cell image count through a scattering intensity threshold and a signal-to-noise ratio threshold.

[0044] For the above steps, the specific implementation in this embodiment is as follows: First, determine a fixed sampling time t. During the process of determining the sampling time, it is necessary to determine it in combination with the performance of the OCTA device and the blood flow velocity magnitudes of the first position 1 and the second position 2 estimated based on experience. The time interval between two samplings needs to ensure that it is not less than the minimum time interval, and the minimum time interval is the time interval that will cause the same red blood cell to be collected in both samplings. Comprehensively consider the scanning object and device performance to determine an appropriate minimum time interval.

[0045] Then, the OCTA device performs image acquisition of duration t at the first position 1 and the second position 2 respectively, and the time intervals of image acquisition are the same, so that a first-position image set and a second-position image set can be obtained respectively. Since the time intervals of the image acquisition rate are the same and the sampling times are also the same, the number of images included in both the first-position image set and the second-position image set is m. In addition, noise reduction and artifact removal processing can be performed on the images in the first-position image set and the second-position image set to improve the quality of the images in the image sets.

[0046] Subsequently, due to blood flow, red blood cells in the blood will flow through the first position 1 and the second position 2. At this time, red blood cells will be scanned in the first position image set and the second position image set, and the brightness of the images of intact red blood cells is relatively high. Here, a brightness threshold is set to determine whether there are red blood cells in the images of the first position image set and the second position image set, and the brightness of the bright part of the image is used as the brightness of the red blood cells.

[0047] Among them, judging whether there are red blood cells by the brightness threshold needs to be combined with the scattering intensity threshold and the signal-to-noise ratio threshold. For the scattering intensity threshold, when the pixel value of a certain part in the image is higher than the scattering intensity threshold determined according to experience, that part is considered to be a blood image; for the signal-to-noise ratio threshold, when the signal-to-noise ratio of a certain part in the image is higher than the signal-to-noise ratio threshold determined according to experience, that part is considered to be an image of red blood cells or blood. In addition, when judging whether there are red blood cells in the image, it is also necessary to combine the flow velocity threshold to determine. When the moving speed of a certain part in the image is lower than the flow velocity threshold, that part is considered not to belong to red blood cells.

[0048] Compare the brightness of red blood cells with the brightness threshold. When the brightness of red blood cells is higher than the brightness threshold and meets the requirements of the scattering intensity threshold and the signal-to-noise ratio threshold, the bright part in the image is considered to be red blood cells. Count the number of images in the first position image set where the brightness of red blood cells at the first position 1 exceeds the brightness threshold, and obtain the number of the first red blood cell images through the scattering intensity threshold and the signal-to-noise ratio threshold ; The situation where there are red blood cells at the first position 1 in the first position image set is as Figure 3 shown, and the situation where there are no red blood cells at the first position 1 in the first position image set is as Figure 4 shown; Count the number of images in the second position image set where the brightness of red blood cells at the second position 2 exceeds the brightness threshold, and obtain the number of the second red blood cell images through the scattering intensity threshold and the signal-to-noise ratio threshold . It is also possible to calculate the proportion of images in the first position image set where the brightness of red blood cells exceeds the brightness threshold to obtain the first red blood cell density ; Calculate the proportion of images in the second position image set where the brightness of red blood cells exceeds the brightness threshold to obtain the second red blood cell density . Since the blood flow velocity slows down, the flow velocity of red blood cells also slows down, resulting in a decrease in the interval between adjacent red blood cells in the front and back, an increase in the proportion of the density of red blood cells per unit blood flow length, and a greater probability of photographing red blood cells at the same time interval. And the blood velocity gradually decreases during the blood flow process. Therefore .

[0049] Next, count the average length of the red blood cells scanned in the first-position image set and the second-position image set, so as to obtain the average length L of the red blood cells. Then, the average red blood cell interval difference can be calculated through the average length of the red blood cells, the number of images included in the first-position image set and the second-position image set, the number of first red blood cell images, and the number of second red blood cell images. : Here, since the faster the blood flow rate, the greater the interval between two red blood cells, therefore .

[0050] S4: Construct the first red blood cell velocity, the second red blood cell velocity, and the red blood cell acceleration. Construct a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Construct a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Solve the first motion equation and the second motion equation to obtain the red blood cell velocity relationship. Further, the purpose of this stage is to construct the first motion equation and the second motion equation, so as to solve the first motion equation and the second motion equation to obtain the red blood cell velocity relationship. Specifically, in step S4, the expression of the first motion equation is: Where is the red blood cell acceleration, is the red blood cell interval difference, is the relative second red blood cell velocity, is the relative first red blood cell velocity. The reference velocities of the relative first red blood cell velocity and the relative second red blood cell velocity are the first red blood cell velocity, so = 0, ; The expression of the second motion equation is: Where is the horizontal azimuth difference, is the second red blood cell velocity, is the first red blood cell velocity. The reference velocities of the first red blood cell velocity and the second red blood cell velocity are 0; The expression of the red blood cell velocity relationship is: .

[0051] For the above steps, the specific implementation in this embodiment is as follows: First, assume that the velocity of the red blood cells at the first position 1 relative to the stationary OCTA device, that is, the first red blood cell velocity is , the speed of the red blood cells at the second position 2 relative to the speed of the stationary OCTA device is the second red blood cell speed is , the reference speed of the first red blood cell speed and the second red blood cell speed is 0; and the average acceleration of the red blood cell in the process of moving from the first position to the second position, that is, the red blood cell acceleration is At this time, we use the first red blood cell speed as the reference speed for speed observation, and we can get the relative first red blood cell speed is 0, relative to the second red blood cell speed is the speed of the red blood cell passing the second position relative to the speed of the first red blood cell, , and the displacement caused by the change in the speed of red blood cells is the red blood cell spacing difference, so the first motion equation can be obtained: Subsequently, we use the speed of the stationary OCTA device as the reference speed for velocity observation. Since the capillaries to be measured are relatively straight and are horizontal in the images obtained by the OCTA device, it can be considered that their displacement is mainly horizontal displacement, and the horizontal displacement can be used to approximately replace the displacement of red blood cells. Thus, the second motion equation can be constructed through the horizontal azimuth difference, red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity: in, is the horizontal azimuth difference. Finally, the first motion equation and the second motion equation are combined and =0, Substituting into the calculation, we can get the red blood cell velocity relationship: It should be noted that, since the capillaries to be tested are relatively straight and are horizontal in the images obtained by the OCTA device, the component of the velocity in the vertical direction is small. Therefore, the first red blood cell velocity and the second red blood cell velocity here are both velocities in the direction of the horizontal azimuth difference, and it can be approximately considered that the first red blood cell velocity and the second red blood cell velocity are the velocities of the red blood cells at the first position 1 and the second position 2, respectively. This error can be corrected in the final calculation of the blood flow velocity.

[0052] S5: construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relation and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0053] Furthermore, the purpose of this stage is to obtain the blood flow rate by solving the differential equation and correcting the calculation result using the vertical position difference. Specifically, first assume that the average speed of the red blood cells in the process of moving from the first position to the second position is , there is a differential relation for the red blood cell acceleration: = = Wherein, represents differentiation.

[0054] Next, for the red blood cell velocity relationship, an auxiliary variable c is constructed for convenience of expression: Therefore, the red blood cell velocity relationship can be written as = . Since the deceleration of blood in the capillary can be considered as a uniformly decelerated process, it can be considered that . Substituting the second motion equation and the red blood cell velocity relationship into the differential relation, the target differential equation can be obtained: = Solving the target differential equation, we can get , wherein, are the undetermined coefficients of the target differential equation. In this embodiment, the undetermined coefficients are obtained by summarizing and inducing past experimental data and calculation results. After obtaining the average velocity of the red blood cells, since the average velocity is obtained according to the horizontal azimuth difference, its velocity is also the velocity in the direction of the horizontal azimuth difference. At this time, since the horizontal azimuth difference and the vertical azimuth difference are known, the angle between the line connecting the first position 1 and the second position 2 and the direction of the horizontal azimuth difference can be obtained according to the trigonometric function relationship. Furthermore, the velocity of the red blood cells on the line connecting the first position 1 and the second position 2 can be obtained according to the trigonometric function relationship. Since the red blood cells flow with the blood and are one of the main components of the blood, the velocity of the red blood cells on the line connecting the first position 1 and the second position 2 can be used as the blood velocity, thereby obtaining the blood flow rate.

[0055] The present invention measures the blood flow rate by collecting images of the first position and the second position and calculating the red blood cell interval difference, and obtains the blood flow rate by calculation, effectively reducing the requirements for the device and the acquisition rate in the process of the OCTA device obtaining the blood flow rate.

[0056] Next, the image-based blood flow rate measurement system provided by the present invention will be described. The image-based blood flow rate measurement system described below can be mutually referred to the image-based blood flow rate measurement method described above.

[0057] Figure 5 Illustrates a schematic structural diagram of the image-based blood flow rate measurement system, as Figure 5As shown, for performing the image-based blood flow velocity measurement method described above, it includes: Capillary to be measured selection module 100: For deploying an OCTA device, selecting a target measurement area through the OCTA device, and selecting a capillary to be measured in the target measurement area through the OCTA device; Azimuth difference measurement module 200: For scanning the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured, selecting a first position and a second position in the image of the capillary to be measured, and obtaining a horizontal azimuth difference and a vertical azimuth difference; Image acquisition module 300: For the OCTA device to acquire images of the first position and the second position, respectively obtaining a first number of red blood cell images and a second number of red blood cell images, and calculating a red blood cell interval difference through the first number of red blood cell images and the second number of red blood cell images; Velocity relationship solving module 400: For constructing a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration, constructing a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, constructing a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, and solving through the first motion equation and the second motion equation to obtain a red blood cell velocity relationship; Blood flow velocity calculation module 500: For constructing a differential relation of the red blood cell acceleration, substituting the red blood cell velocity relationship and the second motion equation into the differential relation to obtain a target differential equation, solving the target differential equation and obtaining the blood flow velocity through the vertical azimuth difference.

[0058] On the other hand, Figure 6 An example of a schematic physical structure of an electronic device is shown, as Figure 6 shown. The electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. Among them, the processor 810, the communication interface 820, and the memory 830 complete mutual communication through the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute the image-based blood flow velocity measurement method, and this method includes: S1: Deploy an OCTA device, select a target measurement area through the OCTA device, and select a capillary to be measured in the target measurement area through the OCTA device; S2: Scan the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured, select a first position and a second position in the image of the capillary to be measured, and obtain a horizontal azimuth difference and a vertical azimuth difference; S3: The OCTA device performs image acquisition on the first position and the second position, respectively obtaining a first red blood cell image quantity and a second red blood cell image quantity, and calculates the red blood cell interval difference based on the first red blood cell image quantity and the second red blood cell image quantity; S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first motion equation based on the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Construct a second motion equation based on the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Solve the first motion equation and the second motion equation to obtain the red blood cell velocity relationship; S5: Construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relationship and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation, and obtain the blood flow velocity based on the vertical azimuth difference.

[0059] In addition, when the logical instructions in the above-mentioned memory 830 can be implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, etc., which can store program codes.

[0060] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the image-based blood flow velocity measurement method provided by the above-mentioned various methods. The method includes: S1: Deploy an OCTA device, select a target measurement area through the OCTA device, and select a capillary to be measured in the target measurement area through the OCTA device; S2: Scan the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured. Select a first position and a second position in the image of the capillary to be measured, and obtain a horizontal azimuth difference and a vertical azimuth difference; S3: The OCTA device performs image acquisition on the first position and the second position, respectively obtaining a first red blood cell image quantity and a second red blood cell image quantity, and calculates the red blood cell interval difference based on the first red blood cell image quantity and the second red blood cell image quantity; S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first motion equation based on the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Construct a second motion equation based on the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Solve the first motion equation and the second motion equation to obtain the red blood cell velocity relationship; S5: Construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relationship and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation, and obtain the blood flow velocity based on the vertical azimuth difference.

[0061] On the other hand, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the image-based blood flow velocity measurement method provided by the above-mentioned various methods. The method includes: S1: Deploy the OCTA device, select a target measurement area through the OCTA device, and select a capillary to be measured in the target measurement area through the OCTA device; S2: Scan the capillary to be measured through the OCTA device to obtain an image of the capillary to be measured, select a first position and a second position in the image of the capillary to be measured, and obtain a horizontal azimuth difference and a vertical azimuth difference; S3: The OCTA device performs image acquisition on the first position and the second position, respectively obtaining a first red blood cell image quantity and a second red blood cell image quantity, and calculates the red blood cell interval difference based on the first red blood cell image quantity and the second red blood cell image quantity; S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first motion equation based on the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Construct a second motion equation based on the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity. Solve the first motion equation and the second motion equation to obtain the red blood cell velocity relationship; S5: Construct the differential relation of the red blood cell acceleration, substitute the red blood cell velocity relation and the second motion equation into the differential relation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0062] The device embodiments described above are merely illustrative. The units described as separation components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0063] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications 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 invention.

Claims

1. An image-based blood flow velocity measurement method, characterized in that: include: S1: deploying an OCTA device, selecting a target measurement area through the OCTA device, and selecting a capillary to be measured in the target measurement area through the OCTA device; S2: scanning the capillary to be tested by the OCTA device to obtain an image of the capillary to be tested, selecting a first position and a second position in the image of the capillary to be tested, and obtaining a horizontal azimuth difference and a vertical azimuth difference; S3: the OCTA device acquires images of the first position and the second position to obtain a first number of red blood cell images and a second number of red blood cell images, respectively, and calculates a red blood cell interval difference according to the first number of red blood cell images and the second number of red blood cell images; S4: constructing a first red blood cell velocity, a second red blood cell velocity and a red blood cell acceleration, constructing a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, constructing a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, and solving the first motion equation and the second motion equation to obtain a red blood cell velocity relationship; S5: construct a differential relation of the red blood cell acceleration, substitute the red blood cell velocity relation and the second motion equation into the differential relation to obtain a target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

2. The method for measuring blood flow velocity based on an image according to claim 1, characterized in that: Step S1 further comprises: S11: deploying the OCTA device, determining a sample to be tested, selecting a target measurement area on the sample to be tested by using the OCTA device, determining a blood vessel distribution status and an observation condition of the target measurement area, and determining a candidate capillary according to the blood vessel distribution status and the observation condition; S12: observing the candidate capillaries by using the OCTA device, and selecting the capillaries to be measured from the candidate capillaries.

3. The method for measuring blood flow velocity based on an image according to claim 1, characterized in that: Step S2 further comprises: S21: scanning the capillary to be tested by the OCTA device to obtain an initial capillary image to be tested, denoising and removing artifacts from the initial capillary image to be tested to obtain a capillary image to be tested, and selecting two ends of a straight capillary in the capillary image to be tested as the first position and the second position; S22: Selecting a first measuring point at the first position and selecting a second measuring point at the second position, the OCTA device measuring the capillary to be measured between the first measuring point and the second measuring point to obtain the horizontal azimuth difference and the vertical azimuth difference.

4. The method for measuring blood flow velocity based on an image according to claim 1, characterized in that: Step S3 further comprises: S31: Determine a sampling time, and collect images of equal duration at the first position and the second position according to the sampling time to obtain a first position image set and a second position image set respectively; S32: Obtain the brightness of red blood cells in the first position image set and the second position image set, determine a brightness threshold, and count the number of images in the first position image set whose red blood cell brightness exceeds the brightness threshold to obtain the number of first red blood cell images, and count the number of images in the second position image set whose red blood cell brightness exceeds the brightness threshold to obtain the number of second red blood cell images; S33: Count the sizes of the red blood cells in the first position image set and the second position image set to obtain the average length of the red blood cells, and calculate the red blood cell spacing difference between the first position and the second position according to the average length of the red blood cells, the number of the first red blood cell images, and the number of the second red blood cell images.

5. The method for measuring blood flow velocity based on an image according to claim 1, characterized in that: In step S4, the expression of the first motion equation is: in, is the red blood cell acceleration, The red blood cell interval difference, is the relative second red blood cell velocity, is the relative first red blood cell velocity, the reference velocity of the relative first red blood cell velocity and the relative second red blood cell velocity is the first red blood cell velocity, so =0, ; The expression of the second motion equation is: in, is the horizontal azimuth difference, is the second red blood cell velocity, is a first red blood cell speed, and a reference speed of the first red blood cell speed and the second red blood cell speed is 0; The expression of the red blood cell velocity relationship is: 。 6. The method for measuring blood flow velocity based on an image according to claim 1, characterized in that: In step S2, the OCTA device obtains the horizontal azimuth difference and the vertical azimuth difference between the first position and the second position by using a pixel coordinate method.

7. The method for measuring blood flow velocity based on an image according to claim 4, characterized in that: In step S31, during the image acquisition process, the time interval between two image acquisitions is not less than the minimum time interval.

8. The method for measuring blood flow velocity based on an image according to claim 4, characterized in that: In step S32, the number of images in the first position image set where the brightness of the red blood cells exceeds the brightness threshold is counted, and the number of first red blood cell images is obtained by using the scattering intensity threshold and the signal-to-noise ratio threshold. The number of images in the second position image set where the brightness of the red blood cells exceeds the brightness threshold is counted, and the number of second red blood cell images is obtained by using the scattering intensity threshold and the signal-to-noise ratio threshold.

9. An image-based blood flow velocity measurement system, used to perform the image-based blood flow velocity measurement method according to any one of claims 1 to 8, characterized in that: include: Capillary selection module to be measured: used for deploying OCTA equipment, selecting a target measurement area through the OCTA equipment, and selecting capillaries to be measured in the target measurement area through the OCTA equipment; Azimuth difference measurement module: used for scanning the capillary to be measured by the OCTA device to obtain an image of the capillary to be measured, selecting a first position and a second position in the image of the capillary to be measured, and obtaining a horizontal azimuth difference and a vertical azimuth difference; Image acquisition module: used for the OCTA device to acquire images of the first position and the second position, respectively obtain the number of first red blood cell images and the number of second red blood cell images, and calculate the red blood cell interval difference according to the number of the first red blood cell images and the number of the second red blood cell images; A velocity relationship solving module: used for constructing a first red blood cell velocity, a second red blood cell velocity and a red blood cell acceleration, constructing a first motion equation through the red blood cell interval difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, constructing a second motion equation through the horizontal azimuth difference, the red blood cell acceleration, the first red blood cell velocity and the second red blood cell velocity, and solving the first motion equation and the second motion equation to obtain a red blood cell velocity relationship; Blood flow rate calculation module: used to construct the differential relationship of the red blood cell acceleration, substitute the red blood cell velocity relationship and the second motion equation into the differential relationship to obtain the target differential equation, solve the target differential equation and obtain the blood flow rate through the vertical azimuth difference.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the image-based blood flow velocity measurement method according to any one of claims 1 to 8 are implemented.

11. A non-transitory 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 image-based blood flow velocity measurement method according to any one of claims 1 to 8 are implemented.

12. A computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, characterized in that: When the program instructions are executed by a computer, the computer can perform the steps of the image-based blood flow velocity measurement method according to any one of claims 1 to 8.

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