Image-based methods, systems, devices, products, and media for measuring blood flow velocity.

Abstract

The present application relates to the technical field of image processing, and provides a blood flow rate measurement method, system, device, product and medium based on images, comprising: selecting a capillary to be measured; selecting a first position and a second position on the capillary to be measured, and measuring horizontal and vertical orientation differences; obtaining a first number of red blood cell images and a second number of red blood cell images, respectively, and calculating a red blood cell spacing difference through the first and second numbers of red blood cell images; constructing a first motion equation and a second motion equation, and obtaining a red blood cell velocity relationship through solving the first and second motion equations; constructing a differential relationship of red blood cell acceleration, substituting the red blood cell velocity relationship and the second motion equation into the differential relationship to obtain a target differential equation, and solving the target differential equation to obtain a blood flow rate. The present application can conveniently measure the blood flow rate.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to image-based methods, systems, devices, products and media for measuring blood flow velocity. Background Technology

[0002] In biomedical research and clinical diagnostics, accurate measurement of 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, disease monitoring, and treatment planning of various diseases. Currently, several technologies are applied to blood flow velocity measurement, but each has its own limitations.

[0003] Laser Doppler velocimeters, pulsed optical laser Doppler imaging, and optical Doppler tomography can measure blood flow velocity using the Doppler effect induced by blood flow. These methods offer high accuracy in real-time blood flow velocity detection, but they are subject to stringent measurement environmental requirements and are highly sensitive to the angle between the blood flow and the laser beam, limiting their widespread application in certain scenarios.

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

[0005] Near-infrared spectroscopy, by analyzing blood flow velocity and blood oxygen content, although it cannot directly measure blood flow velocity, provides valuable information on 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] Furthermore, Chinese patent application CN117752298A discloses a method and system for measuring capillary blood flow velocity based on OCTA. This method utilizes the different absorption characteristics of different tissues, plasma, and red blood cells to the spectrum. Capillaries are selected for scanning and imaging on non-invasive retinal OCTA images to acquire and process the absorption spectrum. Blood flow velocity and direction are measured by evaluating the similarity of the spectral absorption curves. While this method solves some measurement challenges to a certain extent, it still has limitations. For example, its reliance on spectral analysis makes the measurement process relatively complex and requires a high level of expertise from both the equipment and the operators. Summary of the Invention

[0007] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this 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 difficulty of operation, eliminate the need for fluorescein injection, calculate flow velocity through image acquisition and processing and mathematical modeling, improve measurement accuracy and stability, and realize capillary blood flow velocity measurement with a wide range of applications.

[0008] This invention provides an image-based method for measuring blood flow velocity, comprising:

[0009] S1: Deploy OCTA equipment, select a target measurement area using the OCTA equipment, and select the capillaries to be measured within the target measurement area using the OCTA equipment;

[0010] S2: The capillary to be tested is scanned by the OCTA device to obtain an image of the capillary to be tested. A first position and a second position are selected in the image of the capillary to be tested, and the horizontal azimuth difference and the vertical azimuth difference are obtained.

[0011] S3: The OCTA device acquires images of the first position and the second position to obtain the first red blood cell image count and the second red blood cell image count, and calculates the red blood cell interval difference based on the first red blood cell image count and the second red blood cell image count.

[0012] S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first equation of motion using 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 equation of motion using 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 equation of motion and the second equation of motion to obtain the red blood cell velocity relationship.

[0013] S5: Construct the differential equation for the acceleration of the red blood cells, substitute the red blood cell velocity relationship and the second equation of motion into the differential equation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0014] According to the image-based blood flow velocity measurement method provided by the present invention, step S1 further includes:

[0015] S11: Deploy the OCTA device, determine the sample to be tested, select a target measurement area on the sample to be tested using the OCTA device, determine the blood vessel distribution and observation conditions of the target measurement area, and determine candidate capillaries based on the blood vessel distribution and observation conditions;

[0016] S12: The candidate capillaries are observed using the OCTA device, and the capillaries to be tested are selected from the candidate capillaries.

[0017] According to the image-based blood flow velocity measurement method provided by the present invention, step S2 further includes:

[0018] S21: The capillary to be tested is scanned by the OCTA device to obtain an initial image of the capillary to be tested. The initial image of the capillary to be tested is denoised and artifacts are removed to obtain an image of the capillary to be tested. The two ends of a straight capillary in the image of the capillary to be tested are selected as the first position and the second position.

[0019] 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.

[0020] According to the image-based blood flow velocity measurement method provided by the present invention, step S3 further includes:

[0021] 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 to obtain the first position image set and the second position image set respectively;

[0022] S32: Obtain the red blood cell brightness in the first location image set and the second location image set, determine the brightness threshold, and count the number of images in the first location image set whose red blood cell brightness exceeds the brightness threshold to obtain the first red blood cell image count; count the number of images in the second location image set whose red blood cell brightness exceeds the brightness threshold to obtain the second red blood cell image count.

[0023] S33: Statistically analyze the size of red blood cells in the first location image set and the second location image set to obtain the average length of red blood cells. Calculate the red blood cell interval difference between the first and second locations using the average length of red blood cells, the number of the first red blood cell images, and the number of the second red blood cell images.

[0024] 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:

[0025] in, For red blood cell acceleration, The difference in erythrocyte septal size, For the relative speed of the second red blood cell, The reference velocity for the relative velocity to the first red blood cell and the relative velocity to the second red blood cell is the first red blood cell velocity. Therefore, =0, ;

[0026] The expression for the second equation of motion is:

[0027]

[0028] in, This is the horizontal azimuth difference. For the second red blood cell velocity, The velocity of the first red blood cell is 0, and the reference velocity for both the first and second red blood cell velocities is 0.

[0029] The expression for the red blood cell velocity relationship is:

[0030] .

[0031] 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 vertical azimuth difference between the first position and the second position using the pixel coordinate method.

[0032] According to the image-based blood flow velocity measurement method provided by the present invention, in step S31, during the image acquisition process, the time interval between two image acquisitions is not less than the minimum time interval.

[0033] 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 location image set whose red blood cell brightness exceeds a brightness threshold is counted, and the number of first red blood cell images is obtained through a scattering intensity threshold and a signal-to-noise ratio threshold.

[0034] The number of images in the second location image set whose red blood cell brightness 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.

[0035] The present invention also provides an image-based blood flow velocity measurement system, comprising:

[0036] Capillary selection module: used to deploy OCTA equipment, select a target measurement area through the OCTA equipment, and select capillaries to be measured in the target measurement area through the OCTA equipment;

[0037] Azimuth difference measurement module: used to scan the capillary to be tested through the OCTA device to obtain an image of the capillary to be tested, select a first position and a second position in the image of the capillary to be tested, and obtain the horizontal azimuth difference and the vertical azimuth difference;

[0038] Image acquisition module: used by 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 based on the number of first red blood cell images and the number of second red blood cell images;

[0039] 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 equation of motion using 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 equation of motion using 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 by solving the first equation of motion and the second equation of motion.

[0040] Blood flow velocity calculation module: used to construct the differential relationship of the red blood cell acceleration, substitute the red blood cell velocity relationship and the second equation of motion into the differential relationship to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0041] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described image-based blood flow velocity measurement methods.

[0042] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the image-based blood flow velocity measurement method as described above.

[0043] The present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to perform the steps of any of the above-described image-based blood flow velocity measurement methods.

[0044] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects:

[0045] The image-based blood flow velocity measurement method, system, device, product, and medium provided by this invention use OCTA equipment to acquire images and measure blood flow velocity through red blood cell interval differences. It does not require continuous tracking of individual red blood cells, thus eliminating the need for high-sampling-rate image acquisition, effectively reducing the requirements for equipment and acquisition rate, and also reducing the probability of measurement failure or measurement errors.

[0046] Furthermore, the method used in this invention does not involve the acquisition of phase difference, thereby effectively improving the acquisition range applicable to this invention. It can adapt to more types of capillaries, and blood flow velocity can be calculated simply by calculating the positional relationship through the pixel information of the image. Therefore, it is more adaptable and improves the adaptability of this invention to different environments.

[0047] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0049] Figure 1 This is a schematic flowchart of the image-based blood flow velocity measurement method provided by the present invention.

[0050] Figure 2 This is a schematic diagram of the first and second positions of the image-based blood flow velocity measurement method provided by the present invention;

[0051] Figure 3 This is a schematic diagram showing the presence of red blood cells at a first position in the first position image set of the image-based blood flow velocity measurement method provided by the present invention;

[0052] Figure 4 This is a schematic diagram of a first position in the image set of the image-based blood flow velocity measurement method provided by the present invention, where there are no red blood cells at the first position.

[0053] Figure 5 This is a schematic diagram of the image-based blood flow velocity measurement system provided by the present invention.

[0054] Figure 6 This is a schematic diagram of the structure of the image-based blood flow velocity measurement device provided by the present invention.

[0055] Figure label:

[0056] 1. First position; 2. Second position; 100. Capillary selection module; 200. Azimuth difference measurement module; 300. Image acquisition module; 400. Velocity relationship calculation module; 500. Blood flow velocity calculation module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0058] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0059] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention based on the specific circumstances.

[0060] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0061] The following is combined Figures 1 to 6 Description of embodiments of the present invention:

[0062] Figure 1 This is a flowchart of an image-based blood flow velocity measurement method. First, the target measurement area is selected, and the capillaries to be measured are selected using an OCTA device. Then, the first and second positions are selected, and the horizontal and vertical azimuth differences are obtained. Subsequently, image acquisition is performed, and the red blood cell interval difference is calculated. Next, the first and second motion equations are constructed to obtain the red blood cell velocity relationship. Finally, the target differential equation is obtained and solved to obtain the blood flow velocity.

[0063] S1: Deploy OCTA equipment, select a target measurement area using the OCTA equipment, and select the capillaries to be measured within the target measurement area using the OCTA equipment;

[0064] Furthermore, the objective of this stage is to determine the target measurement area, and then acquire an image of the target measurement area using an OCTA device to identify the capillaries to be measured. Step S1 specifically includes:

[0065] S11: Deploy the OCTA device, determine the sample to be tested, select a target measurement area on the sample to be tested using the OCTA device, determine the blood vessel distribution and observation conditions of the target measurement area, and determine candidate capillaries based on the blood vessel distribution and observation conditions;

[0066] S12: The candidate capillaries are observed using the OCTA device, and the capillaries to be tested are selected from the candidate capillaries.

[0067] The specific implementation method for the above steps in this embodiment is as follows:

[0068] First, the OCTA equipment is deployed, and the object to be observed is determined, serving as the sample to be tested. Since OCTA equipment has specific requirements regarding the permeability and vascular distribution of the observed area in biological tissue, overly complex capillary distributions may interfere with OCTA observations. Furthermore, when measuring blood flow velocity to aid in disease diagnosis, it is also necessary to observe capillaries in potential lesion sites. Therefore, the first step is to use OCTA equipment to select a potential lesion area on the sample with a relatively simple vascular distribution that meets the observation conditions of the OCTA equipment as the target measurement area. Within the target measurement area, several relatively straight, smooth capillary segments without obvious damage or thrombus are initially selected as candidate capillaries.

[0069] Next, the candidate capillaries were observed using an OCTA device to observe and evaluate their straightness, integrity, and permeability. The capillaries with the highest straightness, integrity, and permeability were selected as the capillaries to be tested.

[0070] S2: The capillary to be tested is scanned by the OCTA device to obtain an image of the capillary to be tested. A first position and a second position are selected in the image of the capillary to be tested, and the horizontal azimuth difference and the vertical azimuth difference are obtained.

[0071] Furthermore, the objective of this stage is to select a first position and a second position, and calculate the horizontal and vertical azimuth differences between the first and second positions, in order to provide data for subsequent blood flow velocity measurement. Step S2 specifically includes:

[0072] S21: The capillary to be tested is scanned by the OCTA device to obtain an initial image of the capillary to be tested. The initial image of the capillary to be tested is denoised and artifacts are removed to obtain an image of the capillary to be tested. The two ends of a straight capillary in the image of the capillary to be tested are selected as the first position and the second position.

[0073] 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.

[0074] In addition, in step S2, the OCTA device obtains the horizontal and vertical azimuth differences between the first and second positions using the pixel coordinate method.

[0075] The specific implementation method for the above steps in this embodiment is as follows:

[0076] First, the capillaries to be tested are scanned using an OCTA device to obtain an initial image of the capillaries. Noise reduction and artifact removal are then performed on the image. Here, the capillaries to be tested are positioned horizontally in the image. Two ends of a relatively straight segment of the capillary are selected as the first and second positions. In this embodiment, blood flows from the first position to the second position. The selection of the first and second positions can be done manually or automatically by a computer. The first and second positions of the capillaries to be tested are as follows: Figure 2 As shown.

[0077] Subsequently, a first measurement point is selected at the first location, and a second measurement point is selected at the second location. In this embodiment, the first measurement point is the center point of the capillary to be measured at the first location, and the second measurement point is the center point of the capillary to be measured at the second location. The OCTA device then measures the horizontal and vertical azimuth differences between the first and second locations using the pixel coordinate method.

[0078] The pixel coordinate method involves the OCTA device establishing a Cartesian coordinate system within the scanned image. In this embodiment, the origin of the Cartesian 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. The OCTA device then acquires the actual size of the scanned image area, the number of pixels in the image, and the image magnification. Combining the actual size of the image area, the number of pixels, and the image magnification, the length represented by one pixel in the image can be obtained. Subsequently, the OCTA device calculates the number of pixels projected onto the x-axis of the capillary between the first and second measurement points, and multiplies this number by the length represented by one pixel to obtain the horizontal azimuth difference. Similarly, the OCTA device calculates the number of pixels projected onto the y-axis of the capillary between the first and second measurement points, and multiplies this number by the length represented by one pixel to obtain the vertical azimuth difference.

[0079] S3: The OCTA device acquires images of the first position and the second position to obtain the first red blood cell image count and the second red blood cell image count, and calculates the red blood cell interval difference based on the first red blood cell image count and the second red blood cell image count.

[0080] Furthermore, the objective of this stage is to acquire images at the first and second positions to obtain the number of red blood cells in the first and second images, and then calculate the red blood cell interval difference so that it can be used for subsequent calculations. Step S3 specifically includes:

[0081] 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 to obtain the first position image set and the second position image set respectively;

[0082] S32: Obtain the red blood cell brightness in the first location image set and the second location image set, determine the brightness threshold, and count the number of images in the first location image set whose red blood cell brightness exceeds the brightness threshold to obtain the first red blood cell image count; count the number of images in the second location image set whose red blood cell brightness exceeds the brightness threshold to obtain the second red blood cell image count.

[0083] S33: Statistically analyze the size of red blood cells in the first location image set and the second location image set to obtain the average length of red blood cells. Calculate the red blood cell interval difference between the first and second locations using the average length of red blood cells, the number of the first red blood cell images, and the number of the second red blood cell images.

[0084] In step S31, during the image acquisition process, the time interval between two image acquisitions is not less than the minimum time interval.

[0085] In step S32, the number of images in the first location image set whose red blood cell brightness exceeds a brightness threshold is counted, and the number of first red blood cell images is obtained through a scattering intensity threshold and a signal-to-noise ratio threshold.

[0086] The number of images in the second location image set whose red blood cell brightness 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.

[0087] The specific implementation method for the above steps in this embodiment is as follows:

[0088] First, a fixed sampling time t is determined. This determination requires considering the performance of the OCTA equipment and the estimated blood flow velocities at positions 1 and 2 based on experience. The time interval between two samplings must be no less than a minimum time interval, which is the interval at which the same red blood cell will be collected in both samplings. A suitable minimum time interval is determined by comprehensively considering the scanned object and the equipment performance.

[0089] Next, the OCTA device acquires images at positions 1 and 2 for a duration of t, with the acquisition time interval being the same. This yields image sets for the first and second positions, respectively. Since the acquisition rate and sampling time are identical, both the first and second position image sets contain m images. Furthermore, noise reduction and artifact removal processes can be applied to the images in both sets to improve their quality.

[0090] 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 image of the complete red blood cell will have a higher brightness. Here, a brightness threshold is set to determine whether red blood cells exist in the images of the first position image set and the second position image set, and the brightness of the bright part in the image is taken as the brightness of the red blood cell.

[0091] The determination of the presence of red blood cells using brightness thresholds requires combining scattering intensity thresholds and signal-to-noise ratio (SNR) thresholds. For the scattering intensity threshold, if the pixel value of a certain portion of the image exceeds an empirically determined scattering intensity threshold, that portion is considered a blood image. For the SNR threshold, if the SNR of a certain portion of the image exceeds an empirically determined SNR threshold, that portion is considered an image of red blood cells or blood. Furthermore, the determination of the presence of red blood cells also requires combining flow velocity thresholds; if the movement velocity of a certain portion of the image is lower than the flow velocity threshold, that portion is considered not to belong to red blood cells.

[0092] The brightness of red blood cells is compared with a brightness threshold. When the brightness of red blood cells exceeds 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 a red blood cell. The number of images in the first position 1 of the first position image set whose red blood cell brightness exceeds the brightness threshold is counted, and the number of first red blood cell images is obtained by applying the scattering intensity threshold and the signal-to-noise ratio threshold. The case where red blood cells are present at position 1 in the first position image set is as follows: Figure 3 As shown, in the first position image set, there are no red blood cells at position 1. Figure 4 As shown; count the number of images in the second position image set where the red blood cell brightness exceeds a brightness threshold, and obtain the number of second red blood cell images by using a scattering intensity threshold and a signal-to-noise ratio threshold. It can also calculate the proportion of images in the first location image set where the red blood cell brightness exceeds a brightness threshold, thus obtaining the first red blood cell density. ; Calculate the proportion of images in the second location image set where the red blood cell brightness exceeds a brightness threshold, and obtain the second red blood cell density. Because blood flow slows down, red blood cell flow also slows down, resulting in smaller intervals between adjacent red blood cells. This increases the density of red blood cells per unit length of blood flow, making it more likely that red blood cells will be captured in a photograph within the same time interval. Furthermore, the speed of blood gradually decreases during flow, therefore... .

[0093] Next, the average length of red blood cells scanned in the first and second position image sets is calculated to obtain the average red blood cell length L. Then, the average red blood cell interval difference can be calculated using the average red blood cell length, the number of images included in the first and second position image sets, the number of first red blood cell images, and the number of second red blood cell images. :

[0094]

[0095] Here, because the faster the blood flow, the larger the gap between two red blood cells, therefore... .

[0096] S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first equation of motion using 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 equation of motion using 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 equation of motion and the second equation of motion to obtain the red blood cell velocity relationship.

[0097] Furthermore, the objective of this stage is to construct a first equation of motion and a second equation of motion, thereby obtaining the red blood cell velocity relationship through solving the first and second equations of motion. Specifically, in step S4, the expression for the first equation of motion is:

[0098] in, For red blood cell acceleration, The difference in erythrocyte septal size, For the relative speed of the second red blood cell, The reference velocity for the relative velocity to the first red blood cell and the relative velocity to the second red blood cell is the first red blood cell velocity. Therefore, =0, ;

[0099] The expression for the second equation of motion is:

[0100]

[0101] in, This is the horizontal azimuth difference. For the second red blood cell velocity, The velocity of the first red blood cell is 0, and the reference velocity for both the first and second red blood cell velocities is 0.

[0102] The expression for the red blood cell velocity relationship is:

[0103] .

[0104] The specific implementation method for the above steps in this embodiment is as follows:

[0105] First, assume the velocity of the red blood cell at position 1 relative to the stationary OCTA device is, i.e., the velocity of the first red blood cell is... The velocity of the red blood cell at position 2 relative to the stationary OCTA device is the velocity of the second red blood cell. The reference velocities for the first and second red blood cells are 0; and the average acceleration of the red blood cell during its journey from the first position to the second position, i.e., the red blood cell acceleration, is... At this point, by using the velocity of the first red blood cell as the reference velocity for velocity observation, we can obtain the relative velocity of the first red blood cell. The value is 0, relative to the second red blood cell velocity. This is the velocity of the red blood cell at the second position relative to the first red blood cell. Furthermore, the displacement caused by the change in the velocity of red blood cells is the difference in the intercellular spaces, therefore the first equation of motion can be obtained:

[0106] Subsequently, we used the velocity of the stationary OCTA device as the reference velocity for velocity observation. Since the capillaries under test are relatively straight and appear to be horizontal in the images acquired by the OCTA device, their displacement can be considered to be mainly horizontal. The horizontal displacement can be used to approximate the displacement of the red blood cells. Thus, the second equation of motion can be constructed using the horizontal azimuth difference, red blood cell acceleration, first red blood cell velocity, and second red blood cell velocity:

[0107]

[0108] in, Let this be the horizontal azimuth difference. Finally, solve the first and second equations of motion simultaneously, and... =0, By substituting the values ​​and performing calculations, the relationship between red blood cell velocities can be obtained:

[0109]

[0110] It should be noted that, since the capillaries under test are relatively straight and appear to be horizontal in the image acquired by the OCTA device, the vertical component of the velocity is relatively small. Therefore, the first and second red blood cell velocities are both velocities in the direction of horizontal azimuth difference. It can be approximated that the first and second red blood cell velocities are the velocities of red blood cells at the first position 1 and the second position 2, respectively. This error can be corrected in the final calculation of blood flow velocity.

[0111] S5: Construct the differential equation for the acceleration of the red blood cells, substitute the red blood cell velocity relationship and the second equation of motion into the differential equation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0112] Furthermore, the objective of this stage is to obtain the blood flow velocity by solving the differential equation and correcting the calculation results using vertical azimuth difference. Specifically, we first assume that the average velocity of the red blood cells during the process from the first position to the second position is... Then, for the acceleration of red blood cells, we have the differential equation:

[0113] = =

[0114] in, It represents the differential.

[0115] Next, for the relationship of red blood cell velocity, an auxiliary variable c is constructed for ease of expression:

[0116]

[0117] Therefore, the red blood cell velocity relationship can be written as follows: = Since the deceleration of blood in capillaries can be considered a uniform deceleration process, it can be assumed that... Substituting the second equation of motion and the relationship between red blood cell velocities into the differential equation, we can obtain the target differential equation:

[0118] =

[0119] Solving the objective differential equation yields the following results. ,in, The undetermined coefficients of the objective differential equation are obtained in this embodiment by summarizing and generalizing past experimental data and calculation results. After solving for the average velocity of red blood cells, since the average velocity is obtained based on the horizontal azimuth difference, its velocity is also the velocity in the direction of the horizontal azimuth difference. At this time, since the horizontal and vertical azimuth differences 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 trigonometric functions. Then, the velocity of red blood cells on the line connecting the first position 1 and the second position 2 can be obtained according to trigonometric functions. Since red blood cells flow with the blood and are one of the main components of the blood, the velocity of red blood cells on the line connecting the first position 1 and the second position 2 can be taken as the blood velocity, thereby obtaining the blood flow velocity.

[0120] This invention measures blood flow velocity by acquiring images of a first position and a second position and calculating the difference in red blood cell intervals. By obtaining blood flow velocity through calculation, the requirements of OCTA equipment on equipment and acquisition rate are effectively reduced in the process of acquiring blood flow velocity.

[0121] The image-based blood flow velocity measurement system provided by the present invention will be described below. The image-based blood flow velocity measurement system described below can be referred to in correspondence with the image-based blood flow velocity measurement method described above.

[0122] Figure 5 A schematic diagram of an image-based blood flow velocity measurement system is shown, such as... Figure 5 As shown, the method for performing the image-based blood flow velocity measurement method described above includes:

[0123] Capillary selection module 100: used to deploy OCTA equipment, select a target measurement area through the OCTA equipment, and select capillaries to be measured in the target measurement area through the OCTA equipment;

[0124] Azimuth difference measurement module 200: used to scan the capillary to be tested through the OCTA device to obtain an image of the capillary to be tested, select a first position and a second position in the image of the capillary to be tested, and obtain the horizontal azimuth difference and the vertical azimuth difference.

[0125] Image acquisition module 300: used by 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 based on the number of first red blood cell images and the number of second red blood cell images;

[0126] Velocity relationship calculation module 400: used to construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration; construct a first equation of motion using 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 equation of motion using 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 by solving the first equation of motion and the second equation of motion.

[0127] Blood flow velocity calculation module 500: 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 velocity through the vertical azimuth difference.

[0128] on the other hand, Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute an image-based blood flow rate measurement method, which includes:

[0129] S1: Deploy OCTA equipment, select a target measurement area using the OCTA equipment, and select the capillaries to be measured within the target measurement area using the OCTA equipment;

[0130] S2: The capillary to be tested is scanned by the OCTA device to obtain an image of the capillary to be tested. A first position and a second position are selected in the image of the capillary to be tested, and the horizontal azimuth difference and the vertical azimuth difference are obtained.

[0131] S3: The OCTA device acquires images of the first position and the second position to obtain the first red blood cell image count and the second red blood cell image count, and calculates the red blood cell interval difference based on the first red blood cell image count and the second red blood cell image count.

[0132] S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first equation of motion using 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 equation of motion using 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 equation of motion and the second equation of motion to obtain the red blood cell velocity relationship.

[0133] S5: Construct the differential equation for the acceleration of the red blood cells, substitute the red blood cell velocity relationship and the second equation of motion into the differential equation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0134] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0135] On the other hand, the present invention also provides 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, wherein when the program instructions are executed by a computer, the computer is able to execute the image-based blood flow velocity measurement method provided by the above methods, the method comprising:

[0136] S1: Deploy OCTA equipment, select a target measurement area using the OCTA equipment, and select the capillaries to be measured within the target measurement area using the OCTA equipment;

[0137] S2: The capillary to be tested is scanned by the OCTA device to obtain an image of the capillary to be tested. A first position and a second position are selected in the image of the capillary to be tested, and the horizontal azimuth difference and the vertical azimuth difference are obtained.

[0138] S3: The OCTA device acquires images of the first position and the second position to obtain the first red blood cell image count and the second red blood cell image count, and calculates the red blood cell interval difference based on the first red blood cell image count and the second red blood cell image count.

[0139] S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first equation of motion using 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 equation of motion using 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 equation of motion and the second equation of motion to obtain the red blood cell velocity relationship.

[0140] S5: Construct the differential equation for the acceleration of the red blood cells, substitute the red blood cell velocity relationship and the second equation of motion into the differential equation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0141] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the image-based blood flow velocity measurement method provided by the methods described above, the method comprising:

[0142] S1: Deploy OCTA equipment, select a target measurement area using the OCTA equipment, and select the capillaries to be measured within the target measurement area using the OCTA equipment;

[0143] S2: The capillary to be tested is scanned by the OCTA device to obtain an image of the capillary to be tested. A first position and a second position are selected in the image of the capillary to be tested, and the horizontal azimuth difference and the vertical azimuth difference are obtained.

[0144] S3: The OCTA device acquires images of the first position and the second position to obtain the first red blood cell image count and the second red blood cell image count, and calculates the red blood cell interval difference based on the first red blood cell image count and the second red blood cell image count.

[0145] S4: Construct a first red blood cell velocity, a second red blood cell velocity, and a red blood cell acceleration. Construct a first equation of motion using 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 equation of motion using 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 equation of motion and the second equation of motion to obtain the red blood cell velocity relationship.

[0146] S5: Construct the differential equation for the acceleration of the red blood cells, substitute the red blood cell velocity relationship and the second equation of motion into the differential equation to obtain the target differential equation, solve the target differential equation and obtain the blood flow velocity through the vertical azimuth difference.

[0147] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0148] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This 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 cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to 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, The method comprises the following steps: S1: arranging an OCTA device, selecting a target measurement area through the OCTA device, and selecting a to-be-measured capillary through the OCTA device in the target measurement area; S2: scanning the to-be-measured capillary through the OCTA device to obtain a to-be-measured capillary image, selecting a first position and a second position in the to-be-measured capillary image, and obtaining a horizontal orientation difference and a vertical orientation difference; S3: The OCTA device image acquisition at the first position and the second position, respectively, to obtain the first red blood cell image quantity and the second red blood cell image quantity, and calculate the red blood cell interval difference through the first red blood cell image quantity and the second red blood cell image quantity; wherein the red blood cell interval difference The calculation method is: Wherein, the number of images included in the first position image set and the second position image set is m, is the number of first red blood cell images, is the number of second red blood cell images, and L is the average length of red blood cells. 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 orientation difference, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, and obtaining a red blood cell velocity relationship through solving the first motion equation and the second motion equation; The expression of the first motion equation is: wherein, is the red blood cell acceleration, is the red blood cell spacing difference, is the relative second red blood cell velocity, is the relative first red blood cell velocity, the reference velocity for the relative first red blood cell velocity and the relative second red blood cell velocity being the first red blood cell velocity, so that = 0, ; The expression of the second motion equation is: wherein, is the horizontal difference of the water, is the second red blood cell velocity, is the first red blood cell velocity, the reference velocity of the first red blood cell velocity and the second red blood cell velocity being 0; The expression of the red blood cell velocity relationship is: ； S5: constructing a differential relationship of the red blood cell acceleration, substituting the red blood cell velocity relationship and the second motion equation into the differential relationship to obtain a target differential equation, and obtaining a blood flow rate through solving the target differential equation and the vertical orientation difference.

2. The image-based blood flow velocity measurement method of claim 1, wherein, Step S1 further comprises: S11: arranging the OCTA device, determining a to-be-measured sample, selecting a target measurement area through the OCTA device on the to-be-measured sample, determining a blood vessel distribution condition and an observation condition of the target measurement area, and determining a candidate capillary according to the blood vessel distribution condition and the observation condition; S12: observing the candidate capillary through the OCTA device to obtain the to-be-measured capillary from the candidate capillary.

3. The image-based blood flow velocity measurement method of claim 1, wherein, Step S2 further comprises: S21: scanning the to-be-measured capillary through the OCTA device to obtain an initial to-be-measured capillary image, denoising and removing artifacts from the initial to-be-measured capillary image to obtain a to-be-measured capillary image, and selecting two ends of a straight capillary in the to-be-measured capillary image as the first position and the second position; S22: selecting a first measurement point at the first position and a second measurement point at the second position, and measuring the to-be-measured capillary between the first measurement point and the second measurement point through the OCTA device to obtain the horizontal orientation difference and the vertical orientation difference.

4. The image-based blood flow velocity measurement method of claim 1, wherein, Step S3 further comprises: S31: determining a sampling time, and performing image acquisition with equal time lengths 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 red blood cell brightness 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 a first red blood cell image quantity, count the number of images in the second position image set whose red blood cell brightness exceeds the brightness threshold to obtain a second red blood cell image quantity; S33: Count the size of the red blood cells in the first position image set and the second position image set to obtain a red blood cell average length, and calculate the red blood cell interval difference between the first position and the second position by using the red blood cell average length, the first red blood cell image quantity, and the second red blood cell image quantity.

5. The image-based blood flow velocity measurement method of claim 1, wherein, In step S2, the OCTA device obtains the horizontal and vertical azimuth differences between the first position and the second position by using a pixel coordinate method.

6. The image-based blood flow velocity measurement method of claim 4, wherein, In step S31, the time interval between the two image acquisitions is not less than a minimum time interval during the image acquisition.

7. The image-based blood flow velocity measurement method of claim 4, wherein, In step S32, the number of images in the first position image set whose red blood cell brightness exceeds the brightness threshold is counted, and the first red blood cell image quantity is obtained by using a scattering intensity threshold and a signal-to-noise ratio threshold. The number of images in the second position image set whose red blood cell brightness exceeds the brightness threshold is counted, and the second red blood cell image quantity is obtained by using a scattering intensity threshold and a signal-to-noise ratio threshold.

8. An image-based blood flow velocity measurement system for performing an image-based blood flow velocity measurement method according to any one of claims 1 to 7, characterized in that It comprises: A capillary under test selection module for deploying an OCTA device, selecting a target measurement region by using the OCTA device, and selecting a capillary under test in the target measurement region by using the OCTA device; An azimuth difference measurement module for scanning the capillary under test by using the OCTA device to obtain a capillary under test image, selecting a first position and a second position in the capillary under test image, and obtaining a horizontal and vertical azimuth difference; An image acquisition module for the OCTA device 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, respectively, and calculate a red blood cell interval difference by using the first red blood cell image quantity and the second red blood cell image quantity; A velocity relationship solving module 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 by using 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 by using the horizontal and vertical azimuth differences, the red blood cell acceleration, the first red blood cell velocity, and the second red blood cell velocity, and solving a red blood cell velocity relationship by using the first motion equation and the second motion equation; A blood flow rate calculation module for constructing a differential relationship of the red blood cell acceleration, substituting the red blood cell velocity relationship and the second motion equation into the differential relationship to obtain a target differential equation, solving the target differential equation, and obtaining a blood flow rate by using the vertical azimuth difference.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the image-based blood flow rate measurement method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, which is executed by a processor, implements the steps of the image-based blood flow velocity measurement method according to any one of claims 1 to 7.

11. A 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, The computer program, which is executed by a processor, implements the steps of the image-based blood flow velocity measurement method according to any one of claims 1 to 7.

Images