A method, device and storage medium for adaptive mesh division of tubular object

Abstract

The present application provides a method for adaptive meshing of a tubular object, comprising: obtaining a three-dimensional contour model of a target tubular object and the center line of each target lumen of the tubular object; extracting multiple target points from the center line, and determining the cross section of the target lumen of the tubular object corresponding to each target point; for each target point, determining the equivalent diameter of the target lumen of the tubular object at the target point and the stenosis rate of the target lumen of the tubular object at the target point; for each vertex on the three-dimensional contour model, determining the mesh size parameter at the vertex based on the equivalent diameter and stenosis rate of the target lumen of the tubular object at the target point closest to the vertex; and adaptive meshing the target lumen of the tubular object based on the determined mesh size parameter at each vertex. In this way, the present application adaptively sets the mesh size parameter according to the equivalent diameter and stenosis rate of the target lumen of the tubular object, and realizes fully automatic adaptive meshing.

Description

Technical Field

[0001] The present application relates to the technical field of tubular fluid simulation, and in particular to a method, device and storage medium for adaptively dividing a mesh of a tubular object. Background Art

[0002] Meshing is the basis of finite element simulation. Meshing is to divide the surface three-dimensional model into many small tetrahedral units, which is equivalent to using tetrahedrons to fill the interior of the entire model, so that simulation calculations can be performed based on these small tetrahedral units. In the simulation process, the size of the mesh has an important impact on the simulation calculation.

[0003] For fluid simulation of tubular objects, the setting of mesh size is particularly important. Because the diameter and stenosis of tubular objects will change, only by taking these changes into account and setting the mesh size adaptively can the accuracy of fluid simulation be improved. The following takes coronary blood flow simulation as an example to illustrate the adaptive meshing of tubular objects.

[0004] For coronary blood flow simulation, because the main coronary artery starts from the aorta, the diameter of its blood vessel generally follows the rule of becoming thinner and thinner, and there are stenosis and lesions in the coronary artery, the importance of each coronary artery position for the simulation is also inconsistent.

[0005] However, there are usually two existing grid division methods. The first method is to set the grid size in all coronary arteries to a fixed value. However, when it is set to a larger value, the number of grid units is small. For areas with thicker blood vessels, the density of the grid meets the calculation requirements of the simulation, but for areas with thinner blood vessels and stenotic areas, the number of grids is small, which may lead to insufficient simulation calculation accuracy and affect the calculation results of the blood flow reserve fraction (FFR). When it is set to a fixed smaller value, the number of grid units is large. For areas with thinner blood vessels and stenotic areas, the grid density is dense enough, which will increase the overall number of grids a lot, resulting in a particularly long simulation calculation time and consuming more computing resources. The second method in the prior art is to set the grid size in all coronary arteries to a fixed moderate value. The grid density in areas with thinner blood vessels and stenotic areas is guaranteed to a certain extent, which can ensure a certain simulation accuracy, and at the same time, the overall number of grids will not increase much. And on the basis of this method, we will add an encryption ball to the location of stenosis of the blood vessel, and the grid inside the encryption ball is set to a finer grid. The finer grid can ensure the calculation accuracy of the blood flow reserve fraction (FFR) in important areas. However, this type of method requires the identification of the narrow segment, the manual addition of encryption balls in the narrow segment, and the setting of the size of the encryption balls. Because this method introduces manual intervention operations, it will increase the meshing steps and lengthen the meshing step time, and it is impossible to make the meshing method fully automatic. Summary of the invention

[0006] In view of this, the purpose of the present application is to provide a method, device and storage medium for adaptive mesh division of a tubular object, which adaptively sets the size parameters of the mesh according to the equivalent diameter and stenosis rate of the lumen of the tubular object, thereby realizing fully automatic adaptive mesh division, thereby ensuring that the number of meshes in the coarser lumen and the number of meshes in the finer lumen are consistent, thereby ensuring the accuracy and efficiency of the simulation calculation.

[0007] The present application provides a method for adaptively dividing a tubular object into a grid, the method comprising:

[0008] Acquire a three-dimensional contour model of the target tubular object and a center line of each target lumen of the target tubular object;

[0009] Extracting a plurality of target points from the center line, and determining the cross section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object;

[0010] For each target point, based on the cross section of the target lumen corresponding to the target point, determine the equivalent diameter of the target lumen at the target point;

[0011] Determine the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located;

[0012] For each vertex on the three-dimensional contour model, a mesh size parameter at the vertex is determined based on an equivalent diameter of a target lumen at a target point closest to the vertex and a stenosis rate of the target lumen;

[0013] Based on the determined mesh size parameters at each vertex, the target lumen is adaptively meshed.

[0014] Optionally, multiple target points are extracted from the center line by the following steps:

[0015] For each center line, determine the starting point of the center line;

[0016] Starting from the starting point of the center line, points are extracted at a preset interval, and each extracted point is determined as a target point.

[0017] Optionally, for each target point, determining the equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point includes:

[0018] For each target point, based on the cross section of the target lumen corresponding to the target point, determine a circle having the same area as the cross section;

[0019] The diameter of a circle having the same area as the cross-sectional area is determined as the equivalent diameter of the target lumen at the target point.

[0020] Optionally, determining the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumens at all target points on the center line where the target point is located includes:

[0021] For each target point, a linear fitting process is performed on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, and a diameter fitting result of the target lumens corresponding to the target point is determined;

[0022] Determine the fitting diameter of the target lumen at the target point based on the diameter fitting result of the target lumen corresponding to the target point;

[0023] According to the stenosis rate calculation formula, based on the fitting diameter and equivalent diameter of the target lumen at the target point, the stenosis rate of the target lumen at the target point is determined.

[0024] Optionally, the mesh size parameter at the vertex is calculated using the following formula:

[0025] X = a × D × (1-ds%)

[0026] Wherein, X is the grid size parameter; a is the grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

[0027] Optionally, after the target lumen is adaptively grid-divided, the adaptive grid-dividing method further includes:

[0028] The adaptive mesh result of the target lumen obtained after the mesh adaptive division is used to perform fluid dynamics simulation processing to determine the blood flow reserve fraction at each position in the target lumen.

[0029] Optionally, the lumen includes a blood vessel lumen, and the three-dimensional contour model of the target tubular object is obtained by the following steps:

[0030] Acquire an original three-dimensional medical image including the target tubular object after preprocessing;

[0031] Based on the original three-dimensional medical image, generating a centerline of a target lumen of a target tubular object in the original three-dimensional medical image to determine a centerline of each target lumen;

[0032] Based on the center line, the target lumen is segmented from the original three-dimensional medical image to obtain a three-dimensional contour model of the target tubular object.

[0033] The embodiment of the present application further provides a grid adaptive division device for a tubular object, the grid adaptive division device comprising:

[0034] An acquisition module, used for acquiring a three-dimensional contour model of the target tubular object and a center line of each target lumen of the target tubular object;

[0035] A cross-section determination module, used to extract a plurality of target points from the center line, and determine the cross-section of the target lumen corresponding to each target point based on a three-dimensional contour model of the target tubular object;

[0036] An equivalent diameter determination module, for determining, for each target point, an equivalent diameter of the target lumen at the target point based on a cross section of the target lumen corresponding to the target point;

[0037] a stenosis rate determination module, configured to determine the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located;

[0038] A mesh size determination module, for determining, for each vertex on the three-dimensional contour model, a mesh size parameter at the vertex based on an equivalent diameter of a target lumen at a target point closest to the vertex and a stenosis rate of the target lumen;

[0039] The partitioning module is used to perform mesh adaptive partitioning on the target lumen based on the determined mesh size parameters at each vertex.

[0040] Optionally, when the cross-section determination module is used to extract a plurality of target points from the center line, the cross-section determination module is used to:

[0041] For each center line, determine the starting point of the center line;

[0042] Starting from the starting point of the center line, points are extracted at a preset interval, and each extracted point is determined as a target point.

[0043] Optionally, when the equivalent diameter determination module is used to determine, for each target point, the equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point, the equivalent diameter determination module is used to:

[0044] For each target point, based on the cross section of the target lumen corresponding to the target point, determine a circle having the same area as the cross section;

[0045] The diameter of a circle having the same area as the cross-sectional area is determined as the equivalent diameter of the target lumen at the target point.

[0046] Optionally, when the stenosis rate determination module is used to determine the stenosis rate of the target lumen at each target point based on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, the stenosis rate determination module is used to:

[0047] For each target point, a linear fitting process is performed on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, and a diameter fitting result of the target lumens corresponding to the target point is determined;

[0048] Determine the fitting diameter of the target lumen at the target point based on the diameter fitting result of the target lumen corresponding to the target point;

[0049] According to the stenosis rate calculation formula, based on the fitting diameter and equivalent diameter of the target lumen at the target point, the stenosis rate of the target lumen at the target point is determined.

[0050] Optionally, the mesh size determination module is further used to calculate the mesh size parameter at the vertex by the following formula:

[0051] X = a × D × (1-ds%)

[0052] Wherein, X is the grid size parameter; a is the grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

[0053] Optionally, the grid adaptive division device further includes a blood flow reserve fraction determination module, and the blood flow reserve fraction determination module is used to:

[0054] The adaptive mesh result of the target lumen obtained after the mesh adaptive division is used to perform fluid dynamics simulation processing to determine the blood flow reserve fraction at each position in the target lumen.

[0055] Optionally, the lumen includes a blood vessel lumen, and the grid adaptive division device further includes a three-dimensional model construction module, and the three-dimensional model construction module is used to:

[0056] Acquire an original three-dimensional medical image including the target tubular object after preprocessing;

[0057] Based on the original three-dimensional medical image, generating a centerline of a target lumen of a target tubular object in the original three-dimensional medical image to determine a centerline of each target lumen;

[0058] Based on the center line, the target lumen is segmented from the original three-dimensional medical image to obtain a three-dimensional contour model of the target tubular object.

[0059] An embodiment of the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the above-mentioned grid adaptive division method are performed.

[0060] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned grid adaptive partitioning method are executed.

[0061] The embodiments of the present application provide a method, device and storage medium for adaptive mesh division of a tubular object. The method comprises: obtaining a three-dimensional contour model of a target tubular object and a center line of each target lumen of the target tubular object; extracting a plurality of target points from the center line, and determining the cross section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object; determining, for each target point, the equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point; determining the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located; determining, for each vertex on the three-dimensional contour model, a mesh size parameter at the vertex based on the equivalent diameter of the target lumen at the target point closest to the vertex and the stenosis rate of the target lumen; and adaptively meshing the target lumen based on the determined mesh size parameter at each vertex.

[0062] In this way, the present application calculates the equivalent diameter and stenosis rate of each position in the target lumen, and then sets the size parameters of the grid at the corresponding position according to the equivalent diameter and stenosis rate of each position in the target lumen, so that the density of the grid can be adaptively adjusted according to the thickness of the lumen. In this way, any lumen cross section has a similar number of grids, which can reduce the number of grids to reduce the amount of calculation of fluid simulation and maintain a high calculation accuracy. In other words, the number of grids in the thicker lumen and the number of grids in the thinner lumen can be consistent, which means that the number of grids in the thicker blood vessel lumen part will not be too many, thereby reducing the overall number of grids, and the number of grids in the thinner blood vessel lumen part also has enough grids to ensure the accuracy of the simulation calculation, so that high-precision calculation results can be obtained while maintaining high calculation efficiency.

[0063] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0065] Figure 1 A flow chart of a method for adaptively dividing a tubular mesh provided in an embodiment of the present application;

[0066] Figure 2 It is a three-dimensional contour model of the aorta lumen and coronary artery lumen;

[0067] Figure 3 A schematic diagram of the calculation results of the stenosis rate of the target lumen provided in this application;

[0068] Figure 4 A schematic diagram of the mesh adaptive division result of the tubular object provided in this application;

[0069] Figure 5 One of the structural schematic diagrams of a tubular object adaptive grid division device provided in an embodiment of the present application;

[0070] Figure 6 A second structural schematic diagram of a tubular object adaptive grid division device provided in an embodiment of the present application;

[0071] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0072] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0073] There are usually two existing grid division methods. The first method is to set the grid size in all coronary arteries to a fixed value. However, when it is set to a larger value, the number of grid units is small. For areas with thicker blood vessels, the density of the grid meets the calculation requirements of the simulation, but for areas with thinner blood vessels and stenotic areas, the number of grids is small, which may lead to insufficient accuracy of simulation calculations and affect the calculation results of the blood flow reserve fraction (FFR). When it is set to a fixed smaller value, the number of grid units is large. For areas with thinner blood vessels and stenotic areas, the grid density is dense enough, which will increase the overall number of grids a lot, resulting in a particularly long simulation time and consuming more computing resources. The second method in the prior art is to set the grid size in all coronary arteries to a fixed moderate value. The grid density in areas with thinner blood vessels and stenotic areas is guaranteed to a certain extent, which can ensure a certain simulation accuracy, and at the same time, the overall number of grids will not increase much. And on the basis of this method, we will add an encryption ball to the location of stenosis of the blood vessel, and the grid inside the encryption ball is set to a finer grid. The finer grid can ensure the calculation accuracy of the blood flow reserve fraction (FFR) in important areas. However, this type of method requires the identification of the narrow segment, the manual addition of encryption balls in the narrow segment, and the setting of the size of the encryption balls. Because this method introduces manual intervention operations, it will increase the meshing steps and lengthen the meshing step time, and it is impossible to make the meshing method fully automatic.

[0074] Based on this, an embodiment of the present application provides a method for adaptive mesh division of a tubular object, which adaptively sets the size parameters of the mesh according to the equivalent diameter and stenosis rate of the target lumen, thereby realizing fully automatic adaptive mesh division, thereby ensuring that the number of meshes for thicker blood vessels and the number of meshes for thinner blood vessels are consistent, thereby ensuring the accuracy and efficiency of the simulation calculation.

[0075] See also Figure 1 , Figure 1 This is a flow chart of a method for adaptively dividing a tubular mesh provided in an embodiment of the present application. Figure 1 As shown in , the method for adaptively dividing the grid of the vascular lumen provided in the embodiment of the present application includes:

[0076] S101, obtaining a three-dimensional contour model of a target tubular object and a center line of each target lumen of the target tubular object.

[0077] Here, the tubular object refers to an object that is hollow in the middle and allows liquid or gas to flow; the target tubular object may be a water pipe, a trachea, a blood vessel, or the like.

[0078] When the target tubular object is a blood vessel, the target lumen is the lumen of the blood vessel; when a vascular lesion study is performed, the target lumen is the lumen of the blood vessel that needs to be studied for vascular lesions, specifically the lumen of the coronary artery, wherein the lumen of the blood vessel refers to the lumen of the blood vessel, and the centerline of each target lumen obtained can be the centerline data of each target lumen. The three-dimensional contour model includes multiple target lumens.

[0079] For examples, see Figure 2 , Figure 2 It is a three-dimensional contour model of the aorta lumen and coronary artery lumen. Figure 2 As shown in , the target lumens included in the three-dimensional contour model include the left coronary artery lumen, the aortic vascular lumen, the right coronary artery vascular lumen, etc.

[0080] In one embodiment of the present application, a three-dimensional contour model of a target tubular object is obtained by the following steps: obtaining an original three-dimensional medical image including the target tubular object after preprocessing; based on the original three-dimensional medical image, generating a centerline of a target lumen of the target tubular object in the original three-dimensional medical image, and determining the centerline of each target lumen; based on the centerline, segmenting the target lumen from the original three-dimensional medical image to obtain a three-dimensional contour model of the target tubular object.

[0081] Here, the preprocessed original three-dimensional medical image refers to the original three-dimensional medical image that has been preprocessed by filtering, denoising, interpolation, etc. When it is necessary to study the inner cavity of the coronary artery, the original three-dimensional medical image obtained can be a CT image or MRI image of the coronary artery area of ​​the heart.

[0082] After obtaining the pre-processed original three-dimensional medical image, it is necessary to generate the center line of the target lumen to determine the center line of each target lumen.

[0083] Among them, the centerline generation can be divided into two parts: the generation of the centerline position and the calculation of the tangent on the centerline. The generation of the centerline position can be completed by manual or automatic methods. The manual centerline position generation method includes: manually marking the center position points of the tubular object at intervals, and then performing spline interpolation on the obtained points to generate the centerline position. The automatic centerline position generation method includes: the path extraction algorithm based on regional growth plus the shortest path algorithm can be used to automatically generate the centerline position. For calculating the tangent direction of each center point on the center line, the central difference method or other methods can be used to calculate the tangent direction of each center point.

[0084] After determining the center line of each target lumen, in order to obtain a three-dimensional contour model of the tubular object, the target lumen needs to be segmented from the original medical image, wherein the segmentation process can be to segment the contour of the lumen in a direction perpendicular to the center line at intervals along the center line, and the resulting set of contours is the segmentation result of the tubular object, so that the three-dimensional contour model of the target tubular object can be generated based on the 2D contour group using the spline interpolation method.

[0085] In addition, a three-dimensional contour model of the target tubular object can be generated in a three-dimensional manner. Specifically, after obtaining the original medical image, the starting point and end point of the tubular object (target blood vessel) are defined respectively, and then the entire tubular object is segmented using threshold algorithms, region growing, level set methods, etc. Finally, based on the 3D segmentation results, the MarchingCube method is used to generate a three-dimensional contour model of the target tubular object.

[0086] S102, extracting a plurality of target points from the center line, and determining the cross section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object.

[0087] Here, extracting multiple target points from the center line refers to extracting multiple target points from the center line of each target lumen. The cross section of the target lumen corresponding to each target point refers to a plane obtained by vertically cutting the target lumen from the target point.

[0088] Among them, when determining the cross section of the target lumen, it can also be determined by the following steps: for the target point on the center line, intercept the three-dimensional model on the plane perpendicular to the tangent direction of the target point, extract the points where the plane and the three-dimensional model intersect to generate a point set, and connect all the points in the point set with the target point to form multiple line segments. Select any one of them as the starting line segment, and the point of the starting line segment on the contour is used as the starting point, and then sort the line segments according to the angles with the starting line segment, determine the order of the remaining points in the point set, and connect the points in the order of the points to form a new contour. This contour is the cross-sectional contour, and the plane formed is the cross section.

[0089] In one embodiment of the present application, multiple target points are extracted from the center line through the following steps: for each center line, the starting point of the center line is determined; starting from the starting point of the center line, points are extracted at a preset interval, and each extracted point is determined as a target point.

[0090] Here, the starting point of the center line may be the center line of the target lumen to which the center line belongs; and the size of the preset interval may be adaptively selected according to actual needs.

[0091] S103 . For each target point, based on the cross section of the target lumen corresponding to the target point, determine the equivalent diameter of the target lumen at the target point.

[0092] In one embodiment of the present application, for each target point, based on the cross-section of the target lumen corresponding to the target point, determining the equivalent diameter of the target lumen at the target point includes: for each target point, based on the cross-section of the target lumen corresponding to the target point, determining a circle with the same area as the cross-section; and determining the diameter of the circle with the same area as the cross-section as the equivalent diameter of the target lumen at the target point.

[0093] It should be noted that the equivalent diameter is a measurement used to represent the size of a lumen at a certain location, and the value is equal to the diameter of a circle with the same area as the lumen. Thus, the diameter of the circle can be used as the equivalent diameter of the target lumen at that location.

[0094] S104 , determining the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located.

[0095] In one embodiment of the present application, for each target point, based on the equivalent diameter of the target lumen at all target points on the center line where the target point is located, determining the stenosis rate of the target lumen at the target point, includes: for each target point, performing linear fitting processing on the equivalent diameters of the target lumen at all target points on the center line where the target point is located, and determining the diameter fitting result of the target lumen corresponding to the target point; based on the diameter fitting result of the target lumen corresponding to the target point, determining the fitting diameter of the target lumen at the target point; and determining the stenosis rate of the target lumen at the target point based on the fitting diameter and equivalent diameter of the target lumen at the target point according to the stenosis rate calculation formula.

[0096] Here, the reason why the change in the diameter of any blood vessel lumen can be determined by the result of linear fitting is that the diameter of a normal (disease-free) blood vessel generally tapers from the branch entrance to the end of the blood vessel, so it can be assumed that the diameter of the blood vessel meets the requirements of linear change. The equivalent diameter can represent the actual size of the target lumen actually being studied. In this way, when it is necessary to determine the stenosis rate at a certain position of the target lumen, a linear fitting result is obtained by performing a linear fitting on all equivalent diameters of the target lumen, so that the fitting diameter of each position of the target lumen can be determined. Then, when it is necessary to determine the stenosis rate at a certain location (target point position), the stenosis rate calculation formula: stenosis rate = (fitting diameter-equivalent diameter) / fitting diameter can be used to determine the stenosis rate of the target lumen at the target point.

[0097] For examples, see Figure 3 , Figure 3 This is a schematic diagram of the calculation results of the stenosis rate of the target lumen provided in this application. Figure 3 As shown in FIG. 1 , the figure calculates the stenosis rate of the RCA blood vessel, the dotted line is the result of the entire linear fitting, and the dotted line result is the calculated stenosis rate. As shown in the figure, it can be seen that there is a large stenosis in the RCA blood vessel.

[0098] S105 . For each vertex on the three-dimensional contour model, determine a mesh size parameter at the vertex based on the equivalent diameter of the target lumen at the target point closest to the vertex and the stenosis rate of the target blood vessel lumen.

[0099] Here, by traversing the three-dimensional contour model of the target lumen, each vertex on the three-dimensional contour model is determined, and for each vertex, the nearest target point on the nearest center line corresponding to the vertex is found. The equivalent diameter information and stenosis rate information corresponding to the target point (representing the equivalent diameter and stenosis information of the lumen) are taken to calculate the mesh size parameters at the vertex. Among them, the three-dimensional contour model is composed of triangular facets, which means that there are three vertices and three edges on a triangular facet, so there are multiple vertices on the three-dimensional contour model.

[0100] In one embodiment of the present application, the mesh size parameter at the vertex is calculated by the following formula: X=a×D×(1-ds%).

[0101] X is a grid size parameter; a is a grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

[0102] Here, (1-ds%) means the ratio of the lumen diameter to the normal lumen diameter; the ratio adjustment coefficient a is a basic grid coefficient that can be used to adjust the density of the entire grid, and the coefficient can be adaptively set according to actual conditions.

[0103] In addition, experiments show that after introducing the stenosis rate, the accuracy of the adaptive grid FFR combined with the equivalent diameter is much higher than that of the adaptive grid FFR using only the equivalent diameter.

[0104] S106: Based on the determined mesh size parameters at each vertex, adaptively mesh the target lumen.

[0105] In one embodiment of the present application, the adaptive meshing of the target lumen based on the determined mesh size parameters at each vertex includes: inputting the determined mesh size parameters at each vertex into a mesh divider, and adaptive meshing of the target lumen of the target crown through the mesh divider.

[0106] Here, the model with set grid size parameters is input into the grid divider, and the grid is adaptively divided to obtain an adaptive grid division result. The adaptive grid algorithm can adopt the Delaunay grid division algorithm and adjust the grid distribution density according to the adaptive grid size.

[0107] Among them, the mesher is a tool that divides the surface three-dimensional model into many small three-dimensional units based on model data.

[0108] For examples, see Figure 4 , Figure 4 Schematic diagram of the mesh adaptive division result of the tubular object provided in this application, where the tubular object is a blood vessel. Figure 4 As shown, the mesh density is higher in the thinner and narrower locations of the blood vessels, thus ensuring that the number of meshes in the thicker blood vessels is consistent with the number of meshes in the thinner blood vessels.

[0109] In another embodiment of the present application, after the target lumen is adaptively grid divided, the grid adaptive division method further includes: using the adaptive grid result of the target lumen obtained after the grid adaptive division to perform fluid dynamics simulation processing to determine the blood flow reserve fraction at each position in the target lumen.

[0110] Here, fluid simulation is performed based on the results of grid adaptive division and the blood flow reserve fraction is calculated. The simulation calculation is to assign certain initial / boundary conditions to the grid model of the vascular lumen and solve the flow field equations that meet the conditions, thereby obtaining a solution close to the actual blood flow condition.

[0111] The reason why grid division is needed and the blood flow reserve fraction (FFR) is calculated through the grid division is that the blood flow reserve fraction (FFR) of each position of the target blood vessel is solved based on the grid space unit using computational fluid dynamics. Among them, the FFR value can be used for the functional evaluation of the patient's coronary artery diseased blood vessels, which is of great significance in clinical practice.

[0112] An embodiment of the present application provides a method for adaptive mesh division of a tubular object, the method comprising: obtaining a three-dimensional contour model of a target tubular object and a center line of each target lumen of the target tubular object; extracting a plurality of target points from the center line, and determining the cross section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object; for each target point, determining the equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point; determining the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located; for each vertex on the three-dimensional contour model, determining the mesh size parameter at the vertex based on the equivalent diameter of the target lumen at the target point closest to the vertex and the stenosis rate of the target lumen; and adaptive mesh division of the target lumen based on the determined mesh size parameter at each vertex.

[0113] In this way, the present application calculates the equivalent diameter and stenosis rate of each position in the target lumen, and then sets the size parameters of the grid at the corresponding position according to the equivalent diameter and stenosis rate of each position in the target lumen, so that the density of the grid can be adaptively adjusted according to the thickness of the blood vessel lumen. In this way, any lumen cross section has a similar number of grids, which can reduce the number of grids to reduce the amount of calculation for fluid simulation and maintain a high calculation accuracy. In other words, the number of grids for thicker blood vessels and the number of grids for thinner blood vessels can be consistent, which means that the number of grids for the thicker blood vessel part will not be too many, thereby reducing the total number of grids, and the number of grids for the thinner blood vessel part also has enough grids to ensure the accuracy of the simulation calculation, so that high-precision calculation results can be obtained while maintaining high calculation efficiency.

[0114] See also Figure 5 , Figure 6 , Figure 5 This is one of the structural schematic diagrams of a tubular object adaptive grid division device provided in an embodiment of the present application. Figure 6 This is a second structural diagram of a tubular object adaptive grid division device provided in an embodiment of the present application. Figure 5 As shown in , the grid adaptive division device 500 includes:

[0115] An acquisition module 510 is used to acquire a three-dimensional contour model of the target tubular object and a center line of each target lumen of the target tubular object;

[0116] A cross-section determination module 520 is used to extract a plurality of target points from the center line and determine the cross-section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object;

[0117] An equivalent diameter determination module 530 is used to determine, for each target point, an equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point;

[0118] A stenosis rate determination module 540 is used to determine the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located;

[0119] A mesh size determination module 550 is used to determine, for each vertex on the three-dimensional contour model, a mesh size parameter at the vertex based on an equivalent diameter of a target lumen at a target point closest to the vertex and a stenosis rate of the target blood vessel lumen;

[0120] The partitioning module 560 is used to perform mesh adaptive partitioning on the target lumen based on the determined mesh size parameters at each vertex.

[0121] Optionally, when the cross-section determination module 520 is used to extract multiple target points from the center line, the cross-section determination module 520 is used to:

[0122] For each center line, determine the starting point of the center line;

[0123] Starting from the starting point of the center line, points are extracted at a preset interval, and each extracted point is determined as a target point.

[0124] Optionally, when the equivalent diameter determination module 530 is used to determine the equivalent diameter of the target lumen at each target point based on the cross section of the target lumen corresponding to the target point, the equivalent diameter determination module 530 is used to:

[0125] For each target point, based on the cross section of the target lumen corresponding to the target point, determine a circle having the same area as the cross section;

[0126] The diameter of a circle having the same area as the cross-sectional area is determined as the equivalent diameter of the target lumen at the target point.

[0127] Optionally, when the stenosis rate determination module 540 is used to determine the stenosis rate of the target lumen at each target point based on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, the stenosis rate determination module 540 is used to:

[0128] For each target point, a linear fitting process is performed on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, and a diameter fitting result of the target lumens corresponding to the target point is determined;

[0129] Determine the fitting diameter of the target lumen at the target point based on the diameter fitting result of the target lumen corresponding to the target point;

[0130] According to the stenosis rate calculation formula, based on the fitting diameter and equivalent diameter of the target lumen at the target point, the stenosis rate of the target lumen at the target point is determined.

[0131] Optionally, the mesh size determination module 550 is further configured to calculate a mesh size parameter at the vertex using the following formula:

[0132] X = a × D × (1-ds%)

[0133] Wherein, X is the grid size parameter; a is the grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

[0134] Optional, such as Figure 6 As shown, the grid adaptive division device 500 further includes a blood flow reserve fraction determination module 570, and the blood flow reserve fraction determination module 570 is used to:

[0135] The adaptive mesh result of the target lumen obtained after the mesh adaptive division is used to perform fluid dynamics simulation processing to determine the blood flow reserve fraction at each position in the target lumen.

[0136] Optionally, the grid adaptive division device 500 further includes a three-dimensional model construction module 580, and the three-dimensional model construction module 580 is used to:

[0137] Acquire an original three-dimensional medical image including the target tubular object after preprocessing;

[0138] Based on the original three-dimensional medical image, generating a centerline of a target lumen in the original three-dimensional medical image to determine a centerline of each target lumen;

[0139] Based on the center line, the target lumen is segmented from the original three-dimensional medical image to obtain a three-dimensional contour model of the target tubular object.

[0140] See also Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 7 As shown in , the electronic device 700 includes a processor 710 , a memory 720 and a bus 730 .

[0141] The memory 720 stores machine-readable instructions executable by the processor 710. When the electronic device 700 is running, the processor 710 communicates with the memory 720 via the bus 730. When the machine-readable instructions are executed by the processor 710, the above-mentioned Figures 1 to 4 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment, and will not be repeated here.

[0142] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figures 1 to 4 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment, and will not be repeated here.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0144] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0145] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0147] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0148] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for adaptively dividing a tubular object into meshes, characterized in that: The grid adaptive partitioning method comprises: Acquire a three-dimensional contour model of the target tubular object and a center line of each target lumen of the target tubular object; Extracting a plurality of target points from the center line, and determining the cross section of the target lumen corresponding to each target point based on the three-dimensional contour model of the target tubular object; For each target point, based on the cross section of the target lumen corresponding to the target point, determine the equivalent diameter of the target lumen at the target point; Determine the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located; For each vertex on the three-dimensional contour model, a mesh size parameter at the vertex is determined based on an equivalent diameter of a target lumen at a target point closest to the vertex and a stenosis rate of the target lumen; Based on the determined mesh size parameters at each vertex, adaptively meshing the target lumen; The mesh size parameter at this vertex is calculated using the following formula: X = a × D × (1-ds%) Wherein, X is the grid size parameter; a is the grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

2. The grid adaptive partitioning method according to claim 1, characterized in that: Extract multiple target points from the center line by following the steps below: For each center line, determine the starting point of the center line; Starting from the starting point of the center line, points are extracted at a preset interval, and each extracted point is determined as a target point.

3. The grid adaptive partitioning method according to claim 1, characterized in that: The step of determining, for each target point, the equivalent diameter of the target lumen at the target point based on the cross section of the target lumen corresponding to the target point, includes: For each target point, based on the cross section of the target lumen corresponding to the target point, determine a circle having the same area as the cross section; The diameter of a circle having the same area as the cross-sectional area is determined as the equivalent diameter of the target lumen at the target point.

4. The grid adaptive partitioning method according to claim 1, characterized in that: The step of determining the stenosis rate of the target lumen at the target point based on the equivalent diameter of the target lumen at all target points on the center line where the target point is located comprises: For each target point, a linear fitting process is performed on the equivalent diameters of the target lumens at all target points on the center line where the target point is located, and a diameter fitting result of the target lumens corresponding to the target point is determined; Determine the fitting diameter of the target lumen at the target point based on the diameter fitting result of the target lumen corresponding to the target point; According to the stenosis rate calculation formula, based on the fitting diameter and equivalent diameter of the target lumen at the target point, the stenosis rate of the target lumen at the target point is determined.

5. The grid adaptive partitioning method according to claim 1, characterized in that: After the target lumen is adaptively grid-divided, the adaptive grid-dividing method further includes: The adaptive mesh result of the target lumen obtained after the mesh adaptive division is used to perform fluid dynamics simulation processing to determine the blood flow reserve fraction at each position in the target lumen.

6. The grid adaptive partitioning method according to claim 1, characterized in that: The lumen includes a blood vessel lumen, and a three-dimensional contour model of a target tubular object is obtained by the following steps: Acquire an original three-dimensional medical image including the target tubular object after preprocessing; Based on the original three-dimensional medical image, generating a centerline of a target lumen of a target tubular object in the original three-dimensional medical image to determine a centerline of each target lumen; Based on the center line, the target lumen is segmented from the original three-dimensional medical image to obtain a three-dimensional contour model of the target tubular object.

7. A tubular object grid adaptive division device, characterized in that: The grid adaptive division device comprises: An acquisition module, used for acquiring a three-dimensional contour model of the target tubular object and a center line of each target lumen of the target tubular object; A cross-section determination module, used to extract a plurality of target points from the center line, and determine the cross-section of the target lumen corresponding to each target point based on a three-dimensional contour model of the target tubular object; An equivalent diameter determination module, for determining, for each target point, an equivalent diameter of the target lumen at the target point based on a cross section of the target lumen corresponding to the target point; a stenosis rate determination module, configured to determine the stenosis rate of the target lumen at the target point based on the equivalent diameters of the target lumen at all target points on the center line where the target point is located; A mesh size determination module, for determining, for each vertex on the three-dimensional contour model, a mesh size parameter at the vertex based on an equivalent diameter of a target lumen at a target point closest to the vertex and a stenosis rate of the target lumen; A partitioning module, configured to adaptively partition the target lumen into a grid based on the determined grid size parameters at each vertex; The mesh size determination module is also used to calculate the mesh size parameter at the vertex by the following formula: X = a × D × (1-ds%) Wherein, X is the grid size parameter; a is the grid size ratio adjustment coefficient; D is the equivalent diameter of the target lumen at the target point closest to the vertex; ds% is the stenosis rate of the target lumen at the target point closest to the vertex.

8. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the grid adaptive partitioning method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the grid adaptive partitioning method according to any one of claims 1 to 6 are executed.

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