Aortic dissection noninvasive blood flow velocity measurement method, system and equipment and storage medium

Abstract

The invention relates to the technical field of medical image processing, and relates to an aortic dissection noninvasive blood flow velocity measurement method, system and device and a storage medium. The aortic dissection noninvasive blood flow velocity measurement method comprises the following steps: acquiring four-dimensional computed tomography angiography image data to be detected; analyzing the four-dimensional computed tomography angiography image data by using an optical flow method to obtain an aorta blood flow velocity field; analyzing the four-dimensional computed tomography angiography image data, segmenting an aorta image and extracting a center line of the aorta; determining the open area of each position of the aorta according to the aorta image and the center line of the aorta; and determining the instantaneous flow velocity of each position of the aorta according to the aorta blood flow velocity field and the overflowing area of each position of the aorta to obtain a blood flow velocity measurement result. According to the invention, the blood flow velocity of the aorta can be accurately identified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical image processing, and in particular to an aortic dissection non-invasive blood flow velocity measurement method, system, device and storage medium. BACKGROUND

[0002] Aortic dissection (AD) is a serious cardiovascular disease, mainly due to the tear of the intima of the aorta, leading to the blood entering the different layers of the aortic wall, forming a dissection. The formation of the intimal flap is a manifestation of the dissection, which is usually caused by the pressure change of the blood between the intima and the adventitia of the dissection. Aortic dissection is a kind of aortic disease with sudden onset and extremely high mortality. Patients may feel severe chest pain, back pain, and even syncope. If not treated in time, the consequences can be very serious.

[0003] Currently, the clinical classification of aortic dissection is mainly based on Stanford classification. Aortic dissection is divided into Type A Aortic Dissection (TAAD) and Type B Aortic Dissection (TBAD). Type A aortic dissection involving the ascending aorta is the most urgent and fatal type, and the dissection involving the ascending aorta is extremely easy to cause pericardial tamponade, aortic valve insufficiency, coronary artery involvement or poor cerebral perfusion, etc. The preferred treatment is open surgical repair; Type B aortic dissection does not involve the ascending aorta, and usually takes intensive drug therapy. If complications such as rupture, ischemia, persistent pain or uncontrolled hypertension occur, or there are high-risk characteristics such as aortic diameter >4cm, large tear, and significant expansion of the false lumen, then thoracic endovascular repair is recommended. However, whether it is drug conservative treatment, intervention or surgical treatment, the distal residual tear still has the risk of progression and rupture. Studies have shown that the risk of aortic dissection rupture is closely related to the pressure and hemodynamics in the false lumen, and high pressure and high-speed blood flow in the false lumen may increase the possibility of rupture. In patients with chronic aortic dissection in the descending aorta, the hemodynamic parameters of the false lumen are closely related to the presence and extent of thrombosis in the false lumen, so non-invasive measures are very important in patient management.

[0004] The complex pathological features and hemodynamic characteristics of aortic dissection disease pose a great challenge to the navigation of guide wires and catheters in implant surgery. Surgeons must accurately identify the true blood vessel lumen, and determine the position of the anatomical entrance, which is crucial for achieving precise angiography and stent deployment. There are three major pain points in the current aortic dissection diagnosis and treatment system: Firstly, the diagnosis mainly relies on computed tomography angiography (CTA) for anatomical morphology evaluation, which cannot quantify hemodynamic parameters.

[0005] Secondly, intraoperative decision-making lacks real-time blood perfusion data support, limiting the precision of treatment plan formulation and adjustment.

[0006] Thirdly, postoperative follow-up still highly depends on invasive digital subtraction angiography (DSA), increasing the burden and medical risk of patients.

[0007] Studies have shown that true lumen blood flow velocity gradient (Δv) > 0.5 m / s can be used as an independent risk factor for predicting the progression of aortic dissection, but when the true lumen blood flow velocity gradient (Δv) > 0.5 m / s, the blood flow environment is usually complex, and traditional techniques cannot obtain the motion of the aortic wall, the changes of hemodynamics and the expansion of dynamic dissection through conventional imaging methods, so improvement is needed. SUMMARY

[0008] The present application aims to at least solve the technical problems existing in the prior art, and provides an aortic dissection non-invasive blood flow velocity measurement method, system, device and storage medium.

[0009] In a first aspect, the present application provides an aortic dissection non-invasive blood flow velocity measurement method, which comprises: acquiring four-dimensional computed tomography angiography image data to be detected; analyzing the four-dimensional computed tomography angiography image data using an optical flow method to obtain an aortic blood flow velocity field; parsing the four-dimensional computed tomography angiography image data, segmenting the aortic image and extracting the centerline of the aorta; determining the flow area of each position of the aorta according to the aortic image and the centerline of the aorta; determining the instantaneous flow velocity of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta to obtain a blood flow velocity measurement result.

[0010] By adopting the technical scheme, the four-dimensional computer tomography angiography technology has the technical advantages of non-invasiveness, rapid scanning and high space-time resolution, the aortic blood flow velocity field can be estimated by analyzing the four-dimensional computer tomography angiography image data through the optical flow method, and the aortic blood flow velocity field can reflect the dynamic changes of blood flow in real time; the cross-sectional area of the aorta at each position is determined according to the aortic image and the center line of the aorta, and the instantaneous flow velocity at each position of the aorta can be accurately positioned according to the aortic blood flow velocity field and the cross-sectional area of the aorta at each position; by analyzing the four-dimensional computer tomography angiography image data to determine the blood flow velocity measurement result, the risk of infection, thrombus and the like caused by traditional invasive catheter measurement can be avoided; in addition, the method integrates the anatomical information (such as the aortic morphology) of the four-dimensional computer tomography angiography image and the hemodynamic parameters (the aortic blood flow velocity field and the cross-sectional area), which can directly reflect the hemodynamic characteristics of the aorta, rather than indirectly estimating the blood flow velocity of the aorta, so that the measured blood flow velocity measurement result is closer to the real state of the aorta, and the accuracy of the blood flow velocity measurement result is improved.

[0011] Optionally, the step of segmenting the aorta region from the four-dimensional computer tomography angiography image data comprises: inputting the four-dimensional computer tomography angiography image data into a blood vessel image segmentation model, the blood vessel image segmentation model analyzing the four-dimensional computer tomography angiography image data, and outputting a segmentation probability map of the four-dimensional computer tomography angiography image; thresholding the segmentation probability map to obtain a binary mask image of the aorta, and segmenting the aorta region from the four-dimensional computer tomography angiography image according to the binary mask image.

[0012] By adopting the technical scheme, the four-dimensional computer tomography angiography image data is analyzed by the blood vessel image segmentation model and the segmentation probability map is outputted, and the binary mask image of the aorta can be obtained by thresholding the segmentation probability map, so that the aorta region is accurately extracted.

[0013] Optionally, the four-dimensional computer tomography angiography image data comprises a continuous sequence of angiography images, and the spatial coordinates, time frames, spatial resolution and time resolution of the angiography images.

[0014] By adopting the technical scheme, the specific information content contained in the four-dimensional computer tomography angiography image data is clearly defined.

[0015] Optionally, the sequence of angiography images is a time sequence, and the step of extracting the center line of the aorta comprises: The time-averaged image is calculated according to the spatial coordinates and time frames of the angiography images, and the time-averaged image is a three-dimensional image, and each pixel point of the time-averaged image represents the average intensity of the signal at the position of the pixel point in the sequence of angiography images; The time-averaged image is sequentially subjected to denoising processing and enhancement processing to obtain a preprocessed time-averaged image; The preprocessed time-averaged image is processed by using a three-dimensional skeletonization algorithm to obtain a three-dimensional skeleton image of the aorta; The three-dimensional skeleton image of the aorta is analyzed to identify the pixel points corresponding to the center line of the aorta to obtain a set of aortic center line pixel points; The pixel points in the set of aortic center line pixel points are sequentially connected to generate the center line of the aorta.

[0016] By adopting the above technical solution, the specific steps of extracting the center line of the aorta are clarified, the denoising processing of the time-averaged image can reduce the influence of noise on the skeletonization result, the enhancement processing of the time-averaged image can highlight the contrast between the aorta and the surrounding tissue, and the aorta region is more obvious, thereby the accuracy of the three-dimensional skeleton image can be improved, and the extraction accuracy of the aortic center line is further improved.

[0017] Optionally, the calculation formula of the time-averaged image is: ; Wherein, represents the time-averaged image, is the spatial coordinate of the angiography image in the spatial coordinate system axis, is the spatial coordinate of the angiography image in the spatial coordinate system axis, is the spatial coordinate of the angiography image in the spatial coordinate system axis; is the total number of time frames in the time sequence corresponding to the four-dimensional computed tomography angiography image data, is the time frame index.

[0018] By adopting the above technical solution, the calculation method of the time-averaged image is clarified.

[0019] Optionally, the four-dimensional computed tomography angiography image data further includes a computed tomography scan amplitude value of each pixel point of the angiography image, and the determination of the flow area of each position of the aorta according to the aortic image and the center line of the aorta includes: Select a sampling point from the center line of the aorta and reconstruct a normal plane, the normal plane being a plane perpendicular to the axial direction of the aorta; Construct a grid on the normal plane; The flow area at each location of the aorta is determined based on the number of grids and the grid area of ​​the normal plane corresponding to each location of the aortic centerline. The formula for calculating the flow area of ​​the aorta at the sampling point is: A[k,t]= ; Where A[k,t] represents the sampling point at time t on the aortic centerline. The flow area at the point; represents the index of the sampling point on the aortic centerline, and t represents the time frame index; v and v are two orthogonal coordinate axes corresponding to the basis vectors of the normal plane; normal plane The total number of grid cells along the coordinate axes. For the normal plane The grid index for setting the coordinate axis direction; normal plane The total number of grid cells along the coordinate axes. For the normal plane The grid index for setting the coordinate axis direction; This is the amplitude value of the computed tomography scan after resampling. Representation plane The first in the coordinate axis direction The coordinates of each grid point. Representation plane The first in the coordinate axis direction The coordinates of each grid point; Representation plane The spacing between grid points along the coordinate axes. Representation plane The spacing between grid points along the coordinate axes; , Represents the interpolation function. The spatial coordinates of the angiographic image at time t are: The computed tomography amplitude value corresponding to each pixel; Representation plane The first in the coordinate axis direction One point, The first in the coordinate axis direction The grid corresponding to each point.

[0020] By adopting the above technical solution, the calculation method for the flow area at various locations of the aorta has been clarified.

[0021] Optionally, the formula for calculating the instantaneous flow rate at various locations of the aorta is: ; wherein, [k,t] represents the instantaneous flow at the sampling point of the aortic centerline at time t; [k,t] represents the blood flow velocity component in the direction of the normal plane base vector of the blood at the sampling point of the aortic centerline at time t; [k,t] represents the blood flow velocity component in the direction of the normal plane base vector of the blood at the sampling point of the aortic centerline at time t; The instantaneous flow rate calculation expression of each position of the aortic centerline is: , , [k,t] represents the instantaneous flow at the sampling point of the aortic centerline at time t; A[k,t] represents the flow area at the sampling point of the aortic centerline at time t. [k,t] represents the instantaneous flow at the sampling point of the aortic centerline at time t; A[k,t] represents the flow area at the sampling point of the aortic centerline at time t.

[0022] By adopting the technical scheme, the calculation manner of the instantaneous flow at each position of the aorta is determined.

[0023] In a second aspect, the present application provides an aortic dissection non-invasive blood flow rate measurement system, the system comprising: An acquisition module is configured to acquire four-dimensional computed tomography angiography image data to be detected, wherein the four-dimensional computed tomography angiography image data comprises a plurality of continuous angiography images; A blood flow velocity field estimation module is configured to analyze the four-dimensional computed tomography angiography image data by using an optical flow method to obtain an aortic blood flow velocity field; An image segmentation module is configured to parse the four-dimensional computed tomography angiography image data, segment an aortic image, and extract a centerline of the aorta; A processing module is configured to determine a flow area of each position of the aorta according to the aortic image and the centerline of the aorta, wherein the flow area is an area of a plane perpendicular to an axial direction of the aorta; A blood flow rate measurement result generation module is configured to determine an instantaneous flow rate of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta, and obtain a blood flow rate measurement result.

[0024] In a third aspect, the present application provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the aortic dissection non-invasive blood flow rate measurement method described above.

[0025] ​In a fourth aspect, the present application also provides a computer readable storage medium, wherein at least one computer program is stored in the computer readable storage medium, and the at least one computer program is executed by a processor in an electronic device to implement the aortic dissection non-invasive blood flow velocity measurement method.

[0026] To sum up, the present application has the following beneficial technical effects: The four-dimensional computed tomography angiography technology has the technical advantages of non-invasiveness, rapid scanning and high spatio-temporal resolution. The aortic blood flow velocity field can be estimated by analyzing the four-dimensional computed tomography angiography image data through the optical flow method, and the aortic blood flow velocity field can reflect the dynamic changes of blood flow in real time. The cross-sectional area of the aorta at each position is determined according to the aortic image and the center line of the aorta, and the instantaneous flow velocity at each position of the aorta can be accurately positioned according to the aortic blood flow velocity field and the cross-sectional area of the aorta at each position. By analyzing the four-dimensional computed tomography angiography image data to determine the blood flow velocity measurement result, the risk of infection and thrombosis caused by traditional invasive catheter measurement can be avoided. In addition, the present method integrates the anatomical information (such as the aortic morphology) of the four-dimensional computed tomography angiography image and the hemodynamic parameters (aortic blood flow velocity field and cross-sectional area), which can directly reflect the hemodynamic characteristics of the aorta, rather than indirectly estimating the blood flow velocity of the aorta, so that the measured blood flow velocity measurement result is closer to the true state of the aorta, and the accuracy of the blood flow velocity measurement result is improved. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 The flowchart of the aortic dissection non-invasive blood flow velocity measurement method provided by an embodiment of the present application is shown in the figure; Figure 2 The aortic region image segmented based on the four-dimensional computed tomography angiography image data is shown in the figure; Figure 3 The cross-sectional (normal plane) schematic diagram corresponding to different positions of the center line of the aorta is shown in the figure; Figure 4 The structural schematic diagram of the electronic device for implementing the aortic dissection non-invasive blood flow velocity measurement method provided by an embodiment of the present application is shown in the figure.

[0028] Reference signs: 10, processor; 11, memory; 12, communication bus; 13, communication interface.

[0029] The implementation of the present application, functional features and advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0030] Embodiments of the present application are described below in detail with reference to the accompanying drawings, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by reference to the accompanying drawings are exemplary only, and are used only for the purpose of explaining the present application, and are not to be understood as limiting the present application.

[0031] In the description of the present application, it is to be understood that the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0032] In the description of the present application, unless otherwise specified and limited, it is to be noted that the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be mechanical connection or electrical connection, it can be the communication between the two elements, it can be direct connection, or indirect connection through intermediate medium, and the specific meaning of the above terms can be understood by those skilled in the art according to the specific circumstances.

[0033] The complex pathological features and hemodynamic characteristics of aortic dissection disease bring great challenges to the navigation of guide wires and catheters in implantation surgery. Surgeons must accurately identify the true blood vessel lumen and determine the position of the anatomical entrance to achieve accurate angiography and stent deployment.

[0034] Referring to Figure 1 Fig. 1 shows a flowchart of an aortic dissection noninvasive blood flow rate measurement method provided by an embodiment of the present application. In this embodiment, the aortic dissection noninvasive blood flow rate measurement method comprises: S1, acquiring four-dimensional computed tomography angiography image data to be detected.

[0035] The full name of four-dimensional computed tomography angiography in English is 4-dimensions-computed tomography angiography, abbreviated as 4D-CTA. The 4D-CTA technology realizes the recording of the flow process of contrast agent in the blood vessel through the addition of a time dimension parameter, can dynamically observe the cerebral blood vessels and vascular lesions, and at the same time obtain multi-modal data such as plain CT, conventional CTA, CT perfusion imaging, etc. The full name of CT is Computed Tomography, i.e. computed tomography; the full name of CTA is Computed Tomography Angiography, which means CT angiography in Chinese.

[0036] The prior art usually predicts the blood flow velocity of aortic dissection through three-dimensional CTA images or nuclear magnetic resonance images, and in the embodiment, four-dimensional computed tomography angiography image data is used to measure the blood flow velocity of aortic dissection.

[0037] The four-dimensional computed tomography angiography image data includes a continuous angiography image sequence, and the spatial coordinates, time frames, spatial resolution and time resolution of the angiography images, and the angiography image sequence is a time sequence.

[0038] The spatial coordinates of the angiography images are the pixel point indexes on the four-dimensional computed tomography angiography image, and the expression of the spatial coordinates is (x, y, z), wherein, is the spatial coordinates of the four-dimensional computed tomography angiography image in the spatial coordinate system axis, is the spatial coordinates of the four-dimensional computed tomography angiography image in the spatial coordinate system axis, is the spatial coordinates of the four-dimensional computed tomography angiography image in the spatial coordinate system axis; It should be noted that, is the number of pixels of the four-dimensional computed tomography angiography image in the spatial coordinate system along the axis (or the axis), length represents the number of slices along the long axis of the blood vessel, and the specific value of length depends on the scanning range. The running direction of the aorta is basically consistent with the extension direction of the human spine, and the long axis of the blood vessel refers to the axis line consistent with the extension direction of the human spine.

[0039] The symbol is used to represent the time phase of the four-dimensional computed tomography angiography image acquisition, and in the embodiment, , The value of is 1 to 10 in order to correspond to 10 evenly distributed phases of the cardiac cycle of the heart; the cardiac cycle of the heart is composed of a systole and a diastole, from the end diastole to the end systole, and back to the end diastole, and each stage has corresponding manifestations in the electrocardiogram and heart sound; the four-dimensional computed tomography angiography images collected at the 10 evenly distributed phases of the cardiac cycle of the heart can more comprehensively reflect the true situation of the aorta.

[0040] The expression of the spatial resolution of the angiography images is (unit: mm), and the expression of the time resolution of the angiography images is ​​(unit: s); the spatial resolution of the angiography image is used to correspond the pixel space to the actual physical parameter space to obtain the pixel physical parameter; the time resolution refers to the ability of the system to capture dynamic images at consecutive time points; through high time resolution, the dynamic changes of blood vessels in the cardiac cycle or respiratory motion can be accurately captured, and motion artifacts can be reduced. Specifically, the spatial resolution of the angiography image needs to be obtained from the DICOM metadata. The full name of DICOM metadata in English is Digital Imaging and Communications in Medicine Metadata. The term "Metadata" specifically refers to the structured information stored in the DICOM file related to medical images, including patient information, device parameters, scanning protocols, etc. Metadata is standardized information embedded in a medical image file, which is used to describe the technical parameters of the patient, examination, device and image itself. respectively correspond to the Columns (Width), Rows (Height), and Pixel Spacing fields in the DICOM file; wherein Columns represents the number of columns, Rows represents the number of rows, Pixel Spacing represents the pixel spacing, Width represents the width, and Height represents the height.

[0041] Four-dimensional computed tomography angiography technology has the technical advantages of non-invasiveness, rapid scanning, and high spatial and temporal resolution, which helps to observe the movement of the aortic wall, the changes of blood flow dynamics, and the expansion of dynamic dissection. Four-dimensional computed tomography angiography technology performs visual analysis and evaluates the geometric changes after rupture, visualizes the spatial distribution of the intimal flap, and assesses the dissection risk in a complex and realistic blood flow environment, demonstrating the potential of analyzing complex aortic dissection.

[0042] Four-dimensional computed tomography angiography technology can display small tears through multi-planar reconstruction (MPR) technology, providing accurate tear location information for endovascular repair. The measurement of adjacent branch and proximal and distal blood flow velocity helps to assess the impact of stent implantation on the blood flow environment after sealing the tear.

[0043] Four-dimensional computed tomography angiography image data can be acquired by a multi-row spiral CT device. The acquired four-dimensional computed tomography angiography image data can be manually imported from an external device by a detection personnel, or received through a cloud platform, or acquired in other ways. In this embodiment, the acquisition method of the four-dimensional computed tomography angiography image data is not limited.

[0044] S2, analyzing the four-dimensional computed tomography angiography image data by using the optical flow method to obtain the aortic blood flow velocity field.

[0045] The step of estimating the aortic blood flow velocity field from the four-dimensional computed tomography angiography image data by using the optical flow method is as follows: The expression of the angiography image collected at t time is denoted as The expression of the aortic blood flow velocity field at t time is denoted as ; t time represents the time phase of the cardiac cycle corresponding to the cardiac cycle when the angiography image is collected.

[0046] Suppose that the brightness is conserved, then The solution of the aortic blood flow velocity field by using the optical flow method is to solve the velocity component .

[0047] For adjacent time frames t and t+1, the following is calculated: wherein, is the gradient of the angiography image in the axis direction, is the gradient of the angiography image in the axis direction, is the gradient of the angiography image in the axis direction, is the time gradient of the angiography image, is the cumulative symbol, denotes a matrix; the purpose of calculating is to determine the spatial gradient change of the angiography image at adjacent time frames t and t+1.

[0048] Through the spatial gradient change of the angiography image at adjacent time frames t and t+1, by solving the optical flow field of all pixels in the angiography image of the adjacent time frames, a continuous blood flow velocity distribution map is generated, so as to obtain the aortic blood flow velocity field .

[0049] In the preferred embodiment of the present embodiment, after obtaining the aortic blood flow velocity field , the aortic blood flow velocity field is subjected to regularization processing, the continuity of the aortic blood flow velocity field is constrained by adding a smoothing term, and the calculation expression for the regularization processing of the aortic blood flow velocity field is as follows: ; wherein, denotes the gradient of , the gradient is a vector, and points to the direction in which the function increases fastest, The magnitude of the gradient represents the rate of increase. In image processing, the gradient is often used to represent changes in image brightness; express Regarding time The partial derivatives of represent Rate of change over time; " " represents the dot product, which is the sum of the corresponding components of two vectors; λ is the smoothing coefficient, used to balance the weights between the data fidelity term and the smoothing term; This represents the square of the second norm (i.e., the Euclidean norm); Represents the aortic blood flow velocity field The partial derivatives; Represents the velocity field of aortic blood flow Find the minimum value of the expression inside the parentheses.

[0050] The aortic blood flow velocity field estimated by optical flow method Perform regularization to find an optimal velocity field. This optimal velocity field serves as the final aortic blood flow velocity field. In satisfying and and While maintaining a smooth surface, try to keep it as smooth as possible.

[0051] S3. Analyze the four-dimensional computed tomography angiography image data, segment the aortic image, and extract the center line of the aorta.

[0052] Specifically, the segmented aortic region image is as follows: Figure 2 As shown, where, Figure 2 The red curve in the middle aorta region is the center line of the aorta.

[0053] Specifically, the steps for segmenting the aortic region based on four-dimensional computed tomography angiography image data include: S301. Input the four-dimensional computed tomography angiography image data into the vascular image segmentation model. The vascular image segmentation model parses the four-dimensional computed tomography angiography image data and outputs the segmentation probability map of the four-dimensional computed tomography angiography image.

[0054] In this embodiment, the blood vessel image segmentation model is a deep learning model. The deep learning model is used to extract features from the four-dimensional computed tomography angiography image in sequence, generate a segmentation probability map of the four-dimensional computed tomography angiography image, and generate a binary mask based on the segmentation probability map.

[0055] In some examples of this embodiment, the deep learning model can be nnUNet or U-Net. U-Net, which stands for U-shaped network, is a symmetric encoder-decoder architecture based on convolutional neural networks, designed specifically for biomedical image segmentation. nnUNet stands for Self-adapting Framework for U-Net-Based Medical Image Segmentation.

[0056] This application does not impose any restrictions on the use of pre-trained vascular image segmentation models to process four-dimensional computed tomography angiography image data, or on the use of training datasets to train the model parameters of the vascular image segmentation model before inputting four-dimensional computed tomography angiography image data.

[0057] S302. Threshold the segmentation probability map to obtain a binary mask image of the aorta, and segment the aortic region from the four-dimensional computed tomography angiography image based on the binary mask image.

[0058] Thresholding is applied to the probability map, and the probability value of each pixel in the 4D computed tomography angiography image is compared with a preset reference probability value. Pixels with probability values ​​greater than the preset reference probability value are marked as aortic regions, generating a binary mask for the aorta. The formula for comparing the probability value of each pixel in the 4D computed tomography angiography image with the preset reference probability value is as follows: ; in, This represents a four-dimensional computed tomography (CT) angiography image. Used to represent the spatial coordinates of pixels in a four-dimensional computed tomography angiography image. Indicates a time frame; express The spatial location in the 4D computed tomography angiography images acquired at different times is ( (pixels).

[0059] Post-processing operations, such as removing small isolated regions and filling holes, are performed on the generated binary mask to further improve the accuracy and completeness of the segmentation results, resulting in the final binary mask image of the aorta.

[0060] The steps for extracting the centerline of the aorta include: S310. Calculate the time-averaged image based on the spatial coordinates and time frames of the angiography image.

[0061] The time-averaged image is a three-dimensional image, and each pixel point of the time-averaged image represents the average intensity of the signal at the position of the pixel point in the sequence of angiographic images.

[0062] The calculation formula of the time-averaged image is: ; Wherein, represents the time-averaged image, is the spatial coordinate of the angiographic image in the axis coordinate, is the spatial coordinate of the angiographic image in the axis coordinate, is the spatial coordinate of the angiographic image in the axis coordinate. is the total number of time frames in the time sequence corresponding to the four-dimensional computed tomography angiographic image data, is the time frame index.

[0063] S320, sequentially performing denoising processing and enhancement processing on the time-averaged image to obtain a preprocessed time-averaged image.

[0064] Specifically, Gaussian filtering, median filtering and the like are used to remove noise in the image, so as to reduce the influence of noise on the skeletonization result; according to the need, contrast enhancement and the like are performed on the image, so as to highlight the contrast between the aorta and the surrounding tissue, so that the aorta region is more obvious, and the preprocessed time-averaged image is obtained , which provides clearer image data for subsequent skeletonization operation.

[0065] S330, processing the preprocessed time-averaged image by using a three-dimensional skeletonization algorithm to obtain a three-dimensional skeleton image of the aorta.

[0066] Specifically, a suitable three-dimensional skeletonization algorithm is selected, such as a skeletonization algorithm based on distance transformation, a skeletonization algorithm based on thinning and the like. These algorithms remove foreground pixel points in the image iteratively while maintaining the topological structure of the image, and finally obtain the skeleton of the image. The skeletonization algorithm based on distance transformation generates a distance transformation map by calculating the shortest distance (such as Euclidean distance or chessboard distance) from each foreground pixel in a binary image to the nearest background pixel. The skeletonization algorithm based on thinning iteratively deletes edge pixels to gradually reduce thick lines to single-pixel-width skeletons while maintaining the topological structure of the original shape.

[0067] A suitable skeletonization algorithm can be selected according to actual needs, and the present application does not make any limitation; the selected skeletonization algorithm is applied to process the preprocessed time-averaged image . The skeletonization algorithm will gradually remove the preprocessed time-averaged image Non-key points in the aorta are reserved, and the center line structure of the aorta is retained. In the skeletonization process, the skeletonization effect of the aorta region can be corrected by adjusting the parameters of the skeletonization algorithm to obtain an accurate center line.

[0068] The final three-dimensional skeleton image of the aorta contains the center line information of the aorta, and the center line is composed of a series of continuous pixel points, which constitute the center path of the aorta.

[0069] S340, analyze the three-dimensional skeleton image of the aorta, identify the pixel points corresponding to the center line of the aorta, and obtain the aorta center line pixel point set.

[0070] In the three-dimensional skeleton image of the aorta, all pixel points belonging to the center line are identified. These points usually have specific characteristics, such as specific pixel value distribution or connection relationship in their neighborhood; the identified center line pixel points are sorted according to their position coordinates in three-dimensional space to form a discrete point set. Each point can be represented by its coordinates (x, y, z) in the three-dimensional image.

[0071] S350, sequentially connect the pixel points in the aorta center line pixel point set to generate the center line of the aorta.

[0072] The user can observe the structure of the aorta through a visualization software or graphical interface, set the starting point and ending point of the center line, and find the optimal path from the starting point of the aorta center line to the ending point of the aorta center line in three-dimensional space according to the Dijkstra algorithm. This optimal path is the center line path from the starting point to the ending point, which is composed of a series of continuous pixel points, which constitute the center line of the aorta. The Chinese name of Dijkstra algorithm is‌Dijkstra algorithm‌, also known as‌Dijkstra algorithm‌ or‌Dijkstra algorithm‌, which is a greedy algorithm for single-source shortest path problem in weighted graph. Its core goal is to find the shortest path from the starting point to all other nodes in the graph, and the weight of the edge in the graph is non-negative.

[0073] In this embodiment, the expression of the aorta center line path is , the aorta center line path includes continuous pixel points, represents the th pixel point in the aorta center line pixel point set, represents the number of pixel points constituting the aorta center line path, is the index of the pixel point at each position of the aorta center line path; is the three-dimensional coordinates corresponding to the th pixel point on the aorta center line path.

[0074] S4, determining the cross-sectional area of each position of the aorta according to the aorta image and the center line of the aorta.

[0075] The cross-sectional area is the area of a plane perpendicular to the axial direction of the aorta. The four-dimensional computed tomography angiography image data further comprises a computed tomography magnitude value of each pixel point of the computed tomography angiography image. The computed tomography magnitude value, also known as the CT magnitude value, is a key indicator for quantifying tissue density, expressed in Hounsfield units (HU), and its range is usually -1000 to +1000.

[0076] Specifically, the cross-sectional area of each position of the aorta is determined according to the aorta image and the center line of the aorta, comprising: S41, selecting a sampling point from the center line of the aorta, and reconstructing a tangent plane.

[0077] The tangent plane is a plane perpendicular to the axial direction of the aorta, that is, the smallest cross-sectional plane of the aorta passing through the sampling point of the center line of the aorta. Reference Figure 3 , Figure 3 are schematic diagrams of the cross sections (i.e., tangent planes) corresponding to several important positions of the aorta; preferably, the embodiment focuses on selecting the cross-sectional area of the cross section corresponding to the position of the aorta at the connection of the sinus and the tube (corresponding to STJ in Figure 3 ), the position of the aortic arch (corresponding to AA1, AA2, AA3 in Figure 3 ), the position of the dissection rupture (corresponding to RS1, RS2, RS3 in Figure 3 ), the position of the celiac trunk (corresponding to CT in Figure 3 ), the position of the renal artery (corresponding to RA in Figure 3 ), and the position of the common iliac artery (corresponding to CIA in Figure 3 ) when calculating the blood flow velocity of the aorta.

[0078] Specifically, the tangent vector of the tangent plane generated based on the first pixel point of the center line of the aorta is calculated according to the following formula: ; wherein, represents the tangent vector of the tangent plane generated based on the first pixel point of the center line of the aorta, represents the first pixel point in the set of pixel points of the center line of the aorta, represents the first pixel point in the set of pixel points of the center line of the aorta; represents the second norm.

[0079] The tangent vector of the tangent plane generated based on the first The calculation formula of the normal plane basis vector generated by each pixel point is: ; In the embodiment, the basis vector and the basis vector are two orthogonal unit vectors of the normal plane, the basis vector is defined as the horizontal axis of the aortic cross section corresponding to the normal plane, and generally points to the left-right direction of the patient's body; and the basis vector is defined as the vertical axis of the cross section, and generally points to the front-back direction of the patient; is the sampling radius of the normal plane, and is the sampling half-width of the normal plane set to ensure complete coverage of the aortic cross section, and the sampling radius of the normal plane is generally determined according to the prior knowledge or the maximum radius of the aorta estimated from the time-averaged image, and the maximum radius of the cross section at each position of the aorta is generated according to experience to leave a certain margin to generate the final sampling radius, to ensure that the resampled normal plane covers the surrounding image pixels.

[0080] S42, constructing a grid on the normal plane.

[0081] For each pixel point on the aortic centerline, a grid point is generated on the normal plane (u, v); ; denotes the grid corresponding to the first point of the normal plane coordinate axis of the normal plane coordinate axis of the normal plane, is the grid index set along the normal plane coordinate axis direction, is the grid index set along the normal plane coordinate axis direction; denotes the coordinate value of the first grid point in the normal plane coordinate axis direction, denotes the coordinate value of the first grid point in the normal plane coordinate axis direction.

[0082] S43, determining the flow area of each position of the aorta according to the grid number and grid area of the normal plane corresponding to each position of the aortic centerline.

[0083] The calculation formula of the flow area of the aorta at the position of the sampling point is: A[k, t]= ; ​​where A[k, t] represents the cross-sectional area of the aorta at the sampling point on the aorta centerline at time t; represents the index of the sampling point on the aorta centerline, and t represents the time frame index; and v are two orthogonal coordinate axes corresponding to the normal plane basis vectors; according to the coordinate axes and the v coordinate axis, the normal plane is divided into a plurality of uniform grids; is the total number of grids in the direction of the normal plane coordinate axis, is the grid point index in the direction of the normal plane coordinate axis; is the total number of grids in the direction of the normal plane coordinate axis, is the grid point index in the direction of the normal plane coordinate axis, through the value of and the value of , the grid point position coordinates on the normal plane (u, v) can be known; is the computed tomography amplitude value after resampling (i.e., after generating the normal plane based on the pixel points on the aorta centerline ); represents the coordinate value of the grid point in the direction of the normal plane coordinate axis, represents the coordinate value of the grid point in the direction of the normal plane coordinate axis; represents the coordinate value of the grid point in the direction of the normal plane coordinate axis; represents the interval between the grid points in the direction of the normal plane coordinate axis, represents the interval between the grid points in the direction of the normal plane coordinate axis; by calculating the area of all the grid points of the normal plane after resampling and the aorta cross-section overlap, the cross-sectional area of the aorta at the sampling point can be known.

[0084] The velocity component and the computed tomography amplitude value corresponding to the normal plane after resampling (i.e., after generating the normal plane based on the pixel points on the aorta centerline ) are obtained using trilinear interpolation, where the velocity component corresponding to the normal plane after resampling is represented as: ; represents an interpolation function, specifically, is a trilinear interpolation function for extracting an interpolation result at an arbitrary spatial point from three-dimensional grid data, which is obtained by performing trilinear interpolation on the spatial point​ The values corresponding to the 8 surrounding grid points are weighted and averaged, and the result of the interpolation calculation is output. The weights of the weighted average are determined by the distances from the spatial point to each grid point. The pixel point with spatial coordinates in the angiogram image at time t corresponds to the velocity, and specifically, the velocity here refers to the velocity perpendicular to the axial plane of the aorta.

[0085] The computed tomography amplitude value corresponding to the normal plane after resampling is represented as: ; The computed tomography amplitude value corresponding to the pixel point with spatial coordinates in the angiogram image at time t is obtained by trilinear interpolation when sampling to non-continuous values, since the computed tomography amplitude value is a discrete four-dimensional matrix.

[0086] S5, determine the instantaneous flow rate of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta, and obtain the blood flow rate measurement result.

[0087] The calculation formula of the instantaneous flow of each position of the aorta is: wherein, [k, t] represents the instantaneous flow at the sampling point of the aortic centerline at time t; is the blood flow velocity component of the blood along the normal plane basis vector direction at the sampling point of the aortic centerline at time t; ; The calculation expression of the instantaneous flow rate of each position of the aortic centerline is: , is the instantaneous flow rate at the sampling point of the aortic centerline at time t, A[k, t] represents the flow area at the sampling point of the aortic centerline at time t, is the instantaneous flow of each position of the aorta, and the instantaneous flow rate of each position of the aortic centerline is the blood flow rate measurement result.

[0088] The blood flow velocity measurement result determined according to the four-dimensional computer tomography angiography image data can accurately track the dynamic change of the false lumen and timely find the progress of thrombosis; through the monitoring of the blood flow velocity, whether the position of the stent is accurate, whether there is an internal leakage and the aortic reconstruction condition can be determined, early accurate evaluation of postoperative recovery can be assisted, and long-term follow-up strategy can be optimized; the blood flow improvement condition can be directly and intuitively presented by using quantitative data, the treatment effect can be accurately evaluated, and strong support can be provided for subsequent treatment adjustment.

[0089] Based on the same inventive concept, an aortic dissection noninvasive blood flow velocity measurement system is provided in an embodiment of the present application.

[0090] The aortic dissection noninvasive blood flow velocity measurement system can be loaded in an electronic device. According to the functions implemented, the aortic dissection noninvasive blood flow velocity measurement system comprises: An acquisition module is configured to acquire four-dimensional computer tomography angiography image data to be detected; the four-dimensional computer tomography angiography image data comprises a plurality of continuous angiography images; A blood flow velocity field estimation module is configured to analyze the four-dimensional computer tomography angiography image data by using an optical flow method to obtain an aortic blood flow velocity field; An image segmentation module is configured to parse the four-dimensional computer tomography angiography image data, segment an aortic image, and extract a center line of the aorta; A processing module is configured to determine a flow area of each position of the aorta according to the aortic image and the center line of the aorta; the flow area is an area of a plane perpendicular to an axial direction of the aorta; A blood flow velocity measurement result generation module is configured to determine an instantaneous flow velocity of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta to obtain a blood flow velocity measurement result.

[0091] The modules described in the present application can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete a fixed function, and are stored in a memory of the electronic device.

[0092] The various change modes and specific examples in the aortic dissection noninvasive blood flow velocity measurement method provided in the above embodiments are also applicable to the aortic dissection noninvasive blood flow velocity measurement system of the present embodiment. Through the foregoing detailed description of the aortic dissection noninvasive blood flow velocity measurement method, those skilled in the art can clearly know the implementation method of the aortic dissection noninvasive blood flow velocity measurement system in the present embodiment. In order to make the description brief, the implementation method of the aortic dissection noninvasive blood flow velocity measurement system in the present embodiment will not be described in detail here.

[0093] The present application also discloses an electronic device, such as Figure 4As shown is a structural schematic diagram of an electronic device of the method for non-invasive blood flow rate measurement of aortic dissection provided by an embodiment of the present application. The electronic device can include at least one processor 10, a memory 11 in communication connection with the at least one processor, a communication bus 12, and a communication interface 13, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as a method for non-invasive blood flow rate measurement of aortic dissection program.

[0094] In some embodiments, the processor 10 can be composed of integrated circuits, for example, can be composed of a single packaged integrated circuit, or can be composed of multiple packaged integrated circuits with the same function or different functions, including one or more combinations of central processing units (CPU), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (Control Unit) of the electronic device, which connects various components of the entire electronic device through various interfaces and lines, executes programs or modules stored in the memory 11 (such as the method for non-invasive blood flow rate measurement of aortic dissection), and calls data stored in the memory 11, to perform various functions of the electronic device and process data.

[0095] The memory 11 includes at least one type of readable storage medium, including flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 can also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Further, the memory 11 can include both the internal storage unit and the external storage device of the electronic device. The memory 11 can be used not only to store application software and various data installed on the electronic device, such as the code of the method for non-invasive blood flow rate measurement of aortic dissection program, but also to temporarily store data that has been output or will be output.

[0096] The communication bus 12 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11, the at least one processor 10, etc.

[0097] The communication interface 13 is configured to enable communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface can include a wired interface and / or a wireless interface (e.g., a WI-FI interface, a Bluetooth interface, etc.), which is typically configured to establish a communication connection between the electronic device and other electronic devices. The user interface can be a display, an input unit (e.g., a keyboard), and optionally, the user interface can also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch screen, etc. The display can also be appropriately referred to as a display screen or a display unit, which is configured to display information processed in the electronic device and to display a visualized user interface.

[0098] Figure 4 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 4 The structure shown does not constitute a limitation on the electronic device, and the electronic device can include fewer or more components than shown, or some components can be combined, or different components can be arranged.

[0099] For example, although not shown, the electronic device can further include a power supply (e.g., a battery) configured to supply power to each component. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that the power management device can be configured to perform functions such as charge management, discharge management, and power consumption management. The power supply can also include one or more DC or AC power sources, a recharging device, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device can also include various sensors, a Bluetooth module, a Wi-Fi module, etc., which are not described here.

[0100] It should be understood that the embodiments are for illustration only, and the scope of the patent application is not limited by the structure.

[0101] Further, the modules / units integrated in the electronic device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. The computer readable storage medium can be volatile or non-volatile.

[0102] The computer readable storage medium stores a computer program capable of being loaded by a processor and executing the aortic dissection non-invasive blood flow rate measurement method of the above-mentioned embodiments.

[0103] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", "an implementation", "a preferred implementation" or "some examples" and the like means 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 present application. In the present specification, the illustrative expressions 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 any one or more embodiments or examples in a suitable manner.

[0104] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made thereto without departing from the principles and spirit of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method of non-invasive blood flow velocity measurement in aortic dissection, characterized by, The method comprises: acquiring four-dimensional computed tomography angiography image data to be detected; the four-dimensional computed tomography angiography image data comprises a continuous angiography image sequence, and spatial coordinates, a time frame, spatial resolution and time resolution of the angiography image; the angiography image sequence is a time sequence; analyzing the four-dimensional computed tomography angiography image data by using an optical flow method to obtain an aortic blood flow velocity field; parsing the four-dimensional computed tomography angiography image data, segmenting an aortic image and extracting a center line of the aorta; determining a flow area of each position of the aorta according to the aortic image and the center line of the aorta; determining an instantaneous flow rate of each position of the aorta according to the aortic blood flow velocity field and the flow area of each position of the aorta to obtain a blood flow rate measurement result; the step of extracting the center line of the aorta comprises: calculating a time-averaged image according to the spatial coordinates and the time frame of the angiography image; the time-averaged image is a three-dimensional image; each pixel point of the time-averaged image represents an average intensity of a signal at a position of a pixel point in the angiography image sequence; sequentially performing denoising processing and enhancement processing on the time-averaged image to obtain a preprocessed time-averaged image; processing the preprocessed time-averaged image by using a three-dimensional skeletonization algorithm to obtain a three-dimensional skeleton image of the aorta; parsing the three-dimensional skeleton image of the aorta, identifying pixel points corresponding to the center line of the aorta to obtain a set of aortic center line pixel points; sequentially connecting the pixel points in the set of aortic center line pixel points to generate the center line of the aorta.

2. The method of non-invasive blood flow velocity measurement for aortic dissection according to claim 1, wherein, The step of segmenting the aortic region according to the four-dimensional computed tomography angiography image data comprises: inputting the four-dimensional computed tomography angiography image data into a blood vessel image segmentation model; the blood vessel image segmentation model parses the four-dimensional computed tomography angiography image data and outputs a segmentation probability map of the four-dimensional computed tomography angiography image; performing threshold processing on the segmentation probability map to obtain a binary mask image of the aorta, and segmenting the aortic region from the four-dimensional computed tomography angiography image according to the binary mask image.

3. The method of non-invasive blood flow velocity measurement for aortic dissection according to claim 1, wherein, The calculation formula of the time-averaged image is: ； wherein, denotes a time-averaged image, is a blood vessel image in a spatial coordinate system axis coordinate, is a blood vessel image in a spatial coordinate system axis coordinate, is a blood vessel image in a spatial coordinate system axis coordinate; is a total number of time frames in a time sequence corresponding to the four-dimensional computed tomography angiography image data, is a time frame index.

4. The method of non-invasive blood flow velocity measurement for aortic dissection according to any one of claims 1 to 3, wherein The four-dimensional computed tomography angiography image data further comprises a computed tomography scan amplitude value of each pixel point of the angiography image, and the determination of the flow area of each position of the aorta according to the aortic image and the center line of the aorta comprises: selecting a sampling point from the center line of the aorta and reconstructing a normal plane, wherein the normal plane is a plane perpendicular to the axial direction of the aorta; constructing a grid on the normal plane; determining the flow area of each position of the aorta according to the number and area of the grid of the normal plane corresponding to each position of the aortic center line; the calculation formula of the flow area of the aorta at the position of the sampling point is: A[k,t]= ; where A[k, t] represents the cross-sectional area at the sampling point of the aortic centerline at time t; represents the index of the sampling point on the aortic centerline, and t represents the time frame index; and v is the two orthogonal coordinate axes corresponding to the normal plane basis vector; the total number of grids in the normal plane coordinate axis direction, the grid index set along the normal plane coordinate axis direction; the total number of grids in the normal plane coordinate axis direction, the grid index set along the normal plane coordinate axis direction; is the computer tomography amplitude value after resampling, represents the coordinate value of the grid point in the normal plane coordinate axis direction, represents the coordinate value of the grid point in the normal plane coordinate axis direction; represents the interval between grid points in the normal plane coordinate axis direction, represents the interval between grid points in the normal plane coordinate axis direction;​ ， represents an interpolation function, represents a pixel point in the angiography image at time t with spatial coordinates corresponding to a computed tomography magnitude value; represents a plane the first point in the coordinate axis direction, the first grid corresponding to the point in the coordinate axis direction.

5. The method of non-invasive blood flow velocity measurement for aortic dissection according to claim 4, wherein, the calculation formula of the instantaneous flow rate of each position of the aorta is: ； wherein, [k, t] denotes the instantaneous flow at the sampling point of the aortic centerline at time t; [k, t] denotes the instantaneous flow at the sampling point of the aortic centerline at time t; [k, t] denotes the instantaneous flow at the sampling point of the aortic centerline at time t; [k, t] denotes the instantaneous flow at the sampling point of the aortic centerline at time t; the calculation formula of the instantaneous flow rate of each position of the aorta is: , Sampling point at time t along the center line of the aorta The instantaneous flow velocity at point t, A[k,t] represents the sampling point on the aortic centerline at time t. The flow area at that point.

6. An aortic dissection non-invasive blood flow velocity measurement system for implementing the aortic dissection non-invasive blood flow velocity measurement method according to any one of claims 1 to 5, characterized by, comprises: an acquisition module configured to acquire four-dimensional computed tomography angiography image data to be detected; The four-dimensional computer tomography angiography image data comprises a continuous angiography image sequence, and spatial coordinates, a time frame, a spatial resolution and a time resolution of the angiography image, the angiography image sequence being a time sequence; a blood flow velocity field estimation module configured to analyze the four-dimensional computer tomography angiography image data by using an optical flow method to obtain an aortic blood flow velocity field; an image segmentation module configured to parse the four-dimensional computer tomography angiography image data, segment an aortic image and extract a centerline of the aorta; a processing module configured to determine a cross-sectional area of each position of the aorta according to the aortic image and the centerline of the aorta, the cross-sectional area being an area of a plane perpendicular to an axial direction of the aorta; a blood flow velocity measurement result generation module configured to determine a transient flow velocity of each position of the aorta according to the aortic blood flow velocity field and the cross-sectional area of each position of the aorta, and obtain a blood flow velocity measurement result; The step of extracting the centerline of the aorta comprises: calculating a time-averaged image according to the spatial coordinates and the time frame of the angiography image, the time-averaged image being a three-dimensional image, and each pixel point of the time-averaged image representing an average intensity of a signal at a position of the pixel point in the angiography image sequence; sequentially performing denoising processing and enhancement processing on the time-averaged image to obtain a preprocessed time-averaged image; processing the preprocessed time-averaged image by using a three-dimensional skeletonization algorithm to obtain a three-dimensional skeleton image of the aorta; parsing the three-dimensional skeleton image of the aorta, identifying pixel points corresponding to the centerline of the aorta, and obtaining a centerline pixel point set of the aorta; sequentially connecting the pixel points in the centerline pixel point set of the aorta to generate the centerline of the aorta.

7. An electronic device, comprising: The electronic device comprises: at least one processor (10); and a memory (11) connected in communication with the at least one processor (10); The memory (11) stores a computer program executable by the at least one processor (10), and the computer program is executed by the at least one processor (10) to enable the at least one processor (10) to perform the aortic dissection non-invasive blood flow velocity measurement method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the aortic dissection non-invasive blood flow velocity measurement method according to any one of claims 1 to 5.

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