Blood flow numerical simulation method and device, computer equipment and storage medium

Abstract

The invention relates to a blood flow numerical simulation method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring medical tomography image data of a target area, and constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data; carrying out model coupling on the three-dimensional model and the one-dimensional model by adopting an optimized model coupling algorithm to generate a multi-scale coupling model; importing the multi-scale coupling model into an image segmentation model based on SimVascar, and obtaining a three-dimensional grid file and a one-dimensional data file of the multi-scale coupling model through the image segmentation model; and inputting the three-dimensional grid file and the first-dimensional data file into a solver for calculation to obtain blood flow parameter information of the target area. According to the embodiment of the invention, the calculation complexity of the model can be reduced while high calculation efficiency and detail observation capability are considered, and the calculation speed and precision of blood flow numerical simulation are improved.

Description

Technical Field

[0001] The present application belongs to the field of fluid mechanics technology, and in particular relates to a blood flow numerical simulation method, device, computer equipment and storage medium. Background Art

[0002] Human survival is inseparable from blood circulation. In the circulatory system of an adult, there are about 5 liters of blood stored in large and small blood vessels, of which 2 / 3 is in the venous system. Numerical simulation of blood flow is an interdisciplinary research direction that combines the fields of biomedical engineering, fluid mechanics and computer science. It simulates the flow of blood in the human body through numerical methods to help understand the physical mechanism of blood flow, predict and evaluate the occurrence and development of cardiovascular diseases, and guide clinical treatment and surgical operations.

[0003] At present, in large-scale blood flow numerical simulation, a multi-scale coupling model based on a three-dimensional model and a one-dimensional model is mainly established. The three-dimensional model is mostly established under the condition that the three-dimensional is a fluid-solid coupling model. When the three-dimensional model uses a rigid wall, a zero-dimensional model is used to couple the two models. When using a three-dimensional model for calculation, although the details of the lesion area can be observed in detail, it will take up a lot of computing resources, especially when dealing with many distal blood vessels, resulting in slow calculation speed; when using a one-dimensional model for calculation, although the calculation efficiency is high, it is impossible to observe the details of the lesion and other related areas in detail. Summary of the invention

[0004] The present application provides a blood flow numerical simulation method, apparatus, computer equipment and storage medium, aiming to solve at least one of the above-mentioned technical problems in the prior art to a certain extent.

[0005] In order to solve the above problems, this application provides the following technical solutions:

[0006] A blood flow numerical simulation method, comprising:

[0007] Acquire medical tomography image data of a target area, and construct a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data;

[0008] The three-dimensional model and the one-dimensional model are coupled by using an optimized model coupling algorithm to generate a multi-scale coupling model;

[0009] Importing the multi-scale coupling model into the image segmentation model based on SimVascular, and obtaining a three-dimensional grid file and a one-dimensional data file of the multi-scale coupling model through the image segmentation model;

[0010] The three-dimensional grid file and the first-dimensional data file are input into a solver for calculation to obtain blood flow parameter information of the target area.

[0011] The technical solution adopted by the embodiment of the present application also includes: obtaining medical tomography image data of the target area, and constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data, including:

[0012] Perform CT angiography on the target area to obtain CT image data, and reconstruct a three-dimensional model of the target area based on the CT image data.

[0013] The technical solution adopted by the embodiment of the present application also includes: obtaining medical tomography image data of the target area, constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data, and further including:

[0014] The reconstructed three-dimensional model is geometrically processed using a geometric processing algorithm to generate a corresponding one-dimensional model.

[0015] The technical solution adopted in the embodiment of the present application also includes: using a geometric processing algorithm to perform geometric processing on the reconstructed three-dimensional model to generate a corresponding one-dimensional model, specifically:

[0016] The thinner blood vessels in the three-dimensional model are segmented and their center lines are extracted, and a corresponding one-dimensional model is generated according to the center lines; wherein the description equation of the one-dimensional model is:

[0017]

[0018] Among them, Ω 1d represents the one-dimensional blood vessel area, time t∈(0,T], z represents the axial coordinate along the blood vessel, Q, P and A represent the flow, pressure and blood vessel cross-sectional area of ​​the one-dimensional model respectively, represents the time derivative of a variable, represents the derivative of the variable with respect to the axial coordinate, ρ represents the blood flow density, δ represents a parameter related to the velocity profile function on the cross section, and N represents a viscous loss term.

[0019] The technical solution adopted in the embodiment of the present application also includes: the optimized model coupling algorithm is used to perform model coupling on the three-dimensional model and the one-dimensional model to generate a multi-scale coupling model, specifically:

[0020] The three-dimensional model is directly coupled with the one-dimensional model under the three-dimensional rigid wall condition, and the following equation is satisfied at the model coupling:

[0021]

[0022] in, represents the flow velocity in the three-dimensional model, σ represents the stress tensor in the three-dimensional model, is Γ out The normal vector of .

[0023] The technical solution adopted by the embodiment of the present application also includes: importing the multi-scale coupling model into the image segmentation model based on SimVascular, and obtaining the three-dimensional grid file and the one-dimensional data file of the multi-scale coupling model through the image segmentation model, specifically:

[0024] After the multi-scale coupling model is imported into the image segmentation model based on SimVascular, the image segmentation model uses the "Models" module of SimVascular to perform three-dimensional finite element mesh division on the three-dimensional model in the multi-scale coupling model, generate and export the corresponding three-dimensional mesh file, and extract the center line of the one-dimensional model in the multi-scale coupling model, set the one-dimensional finite element mesh unit size, and generate and export a one-dimensional data file including the finite element data coordinates of the center line and bifurcation structure information.

[0025] The technical solution adopted by the embodiment of the present application also includes: the three-dimensional grid file and the first-dimensional data file are input into the solver for calculation to obtain the blood flow parameter information of the target area, specifically:

[0026] The three-dimensional grid file and the first-dimensional data file are input into the svFSIplus_cpl1D solver, and the three-dimensional model is parallelly calculated by the svFSIplus_cpl1D solver to obtain the blood flow parameter information of the target area; wherein the blood flow parameter information includes pressure, flow and wall shear stress.

[0027] Another technical solution adopted by the embodiment of the present application is: a blood flow numerical simulation device, comprising:

[0028] Model building module: used for acquiring medical tomography image data of a target area, and building a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data;

[0029] Model coupling module: used for coupling the three-dimensional model and the one-dimensional model using an optimized model coupling algorithm to generate a multi-scale coupling model;

[0030] File acquisition module: used for importing the multi-scale coupling model into the image segmentation model based on SimVascular, and obtaining the three-dimensional grid file and one-dimensional data file of the multi-scale coupling model through the image segmentation model;

[0031] Blood flow calculation module: used for inputting the three-dimensional grid file and the first-dimensional data file into the solver for calculation to obtain the blood flow parameter information of the target area.

[0032] Another technical solution adopted by the embodiment of the present application is: a computer device, the computer device includes a processor and a memory coupled to the processor, wherein:

[0033] The memory stores program instructions for implementing the blood flow numerical simulation method;

[0034] The processor is used to execute the program instructions stored in the memory to control the blood flow numerical simulation method.

[0035] Another technical solution adopted by the embodiment of the present application is: a storage medium storing program instructions executable by a processor, wherein the program instructions are used to execute the blood flow numerical simulation method.

[0036] Compared with the prior art, the beneficial effects produced by the embodiments of the present application are as follows: the blood flow numerical simulation method, device, computer equipment and storage medium of the embodiments of the present application reconstruct a three-dimensional model of the target area based on medical tomography image data, use a geometric processing algorithm to process the reconstructed three-dimensional model, generate a corresponding one-dimensional model, directly couple with the one-dimensional model under three-dimensional rigid wall conditions to construct a multi-scale coupling model, and use the svFSIplus_cpl1D solver to calculate blood flow parameter information, thereby combining the advantages of the three-dimensional model and the one-dimensional model, being able to reduce the computational complexity of the model while taking into account high computational efficiency and detail observation capabilities, and improve the calculation speed and accuracy of the blood flow numerical simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a flow chart of a blood flow numerical simulation method according to an embodiment of the present application;

[0038] Figure 2 A schematic diagram of constructing a multi-scale coupling model according to an embodiment of the present application;

[0039] Figure 3 A geometric diagram of a multi-scale coupling model according to an embodiment of the present application;

[0040] Figure 4 This is a schematic diagram of the structure of a blood flow numerical simulation device according to an embodiment of the present application;

[0041] Figure 5 A schematic diagram of the computer device structure of an embodiment of the present application;

[0042] Figure 6 A schematic diagram of the structure of a storage medium according to an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0044] The terms "first", "second", "third" in this application are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first", "second", "third" can expressly or implicitly include at least one of the features. In the description of this application, the meaning of "multiple" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In the embodiments of this application, all directional indications (such as up, down, left, right, front, back...) are only used to explain the relative position relationship, movement, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication also changes accordingly. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or computer device that includes a series of steps or units is not limited to the steps or units listed, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or computer devices.

[0045] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0046] Specifically, see Figure 1 , is a flow chart of the blood flow numerical simulation method of the embodiment of the present application. The blood flow numerical simulation method of the embodiment of the present application comprises the following steps:

[0047] S100: Acquire medical tomography image data of a target area, and reconstruct a three-dimensional model of the target area according to the medical tomography image data;

[0048] In this step, the target area is the lesion area or the area of ​​interest of the subject, such as cerebral blood vessels, etc. CT image data is obtained by performing CT angiography on the target area of ​​the subject, and a three-dimensional model of the target area is reconstructed based on the CT image data.

[0049] S110: performing geometric processing on the reconstructed three-dimensional model using a geometric processing algorithm to generate a corresponding one-dimensional model;

[0050] In this step, if Figure 2 As shown, it is a schematic diagram of constructing a multi-scale coupling model of an embodiment of the present application. First, the thinner blood vessels near the outlet of the three-dimensional model are segmented and their center lines are extracted, and the corresponding one-dimensional model is generated according to the center lines; wherein the description equation of the one-dimensional model is:

[0051]

[0052] In formula (1), Ω 1d represents the one-dimensional blood vessel area, time t∈(0,,T], z represents the axial coordinate along the blood vessel, Q, P and A represent the flow, pressure and blood vessel cross-sectional area of ​​the one-dimensional model respectively, represents the time derivative of a variable, represents the derivative of the variable with respect to the axial coordinate, ρ represents the blood flow density, δ represents a parameter related to the velocity profile function on the cross section, and N represents a viscous loss term. In the embodiment of the present application, a form more in line with the characteristics of Poiseuille flow is adopted, and δ=1 / 3 is taken, which can improve the model's ability to describe the actual flow law.

[0053] S120: using an optimized model coupling algorithm to perform model coupling on the three-dimensional model and the one-dimensional model to generate a multi-scale coupling model;

[0054] In this step, the geometric diagram of the multiscale coupling model is as follows: Figure 3 As shown, where Ω 3d and Ω 1d =[a,b] represents the three-dimensional model and the one-dimensional model respectively, Γ ib With Γ out Respectively represent the inlet and outlet of the three-dimensional model. In the embodiment of the present application, the three-dimensional model and the one-dimensional model satisfy the following equation at the model coupling:

[0055]

[0056] In formula (1), represents the flow velocity in the three-dimensional model, σ represents the stress tensor in the three-dimensional model, is Γ out The normal vector of .

[0057] Based on the above, the embodiment of the present application is directly coupled with the one-dimensional model under the three-dimensional rigid wall condition of the three-dimensional model, thereby reducing the computational complexity while taking into account high computational efficiency and detail observation capabilities.

[0058] S130: importing the multi-scale coupling model into the image segmentation model based on SimVascular, performing three-dimensional finite element meshing on the three-dimensional model in the multi-scale coupling model through the image segmentation model to generate a corresponding three-dimensional mesh file, and performing centerline extraction on the one-dimensional model in the multi-scale coupling model to generate a one-dimensional data file;

[0059] In this step, SimVascular is an interactive application used to create patient-specific vascular geometry models from 3D medical imaging data and perform blood flow simulation using various numerical methods. Specifically, after the multi-scale coupling model is imported into the image segmentation model based on SimVascular, the image segmentation model first uses the "Models" module of SimVascular to perform 3D finite element meshing on the 3D model, generates and exports the corresponding 3D mesh file, extracts the centerline of the 1D model, sets the 1D finite element mesh unit size, and generates and exports a 1D data file including the finite element coordinates of the centerline and bifurcation structure information.

[0060] S140: inputting the generated three-dimensional grid file and the first-dimensional data file into a solver for calculation to obtain blood flow parameter information of the target area;

[0061] In this step, the svFSIplus_cpl1D solver is used to calculate the three-dimensional grid file and the first-dimensional data file. The svFSIplus_cpl1D solver uses parallel computing in the three-dimensional model part to generate blood flow parameter information such as pressure, flow, and wall shear stress (WSS) in the target area, thereby greatly improving the computational efficiency of the model.

[0062] S150: Perform visual analysis on the blood flow parameter information, and identify lesions in the target area according to the visual analysis results;

[0063] In this step, Paraview and other post-processing algorithms are used to perform visual analysis on the blood flow parameter information, and lesions in the target area are identified based on the visual analysis results to provide auxiliary diagnosis basis for lesions in the target area.

[0064] Based on the above, the blood flow numerical simulation method of the embodiment of the present application reconstructs a three-dimensional model of the target area based on medical tomography image data, uses a geometric processing algorithm to process the reconstructed three-dimensional model, generates a corresponding one-dimensional model, and directly couples it with the one-dimensional model under three-dimensional rigid wall conditions to construct a multi-scale coupling model, and uses the svFSIplus_cpl1D solver to calculate the blood flow parameter information, thereby combining the advantages of the three-dimensional model and the one-dimensional model. While taking into account high computing efficiency and detail observation capabilities, it can reduce the computational complexity of the model and improve the calculation speed and accuracy of the blood flow numerical simulation.

[0065] See also Figure 4 , is a schematic diagram of the structure of a blood flow numerical simulation device according to an embodiment of the present application. The blood flow numerical simulation method device 40 according to an embodiment of the present application comprises:

[0066] Model building module 41: used for acquiring medical tomography image data of a target area, and building a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data;

[0067] Model coupling module 42: used to couple the three-dimensional model and the one-dimensional model using an optimized model coupling algorithm to generate a multi-scale coupling model;

[0068] File acquisition module 43: used for importing the multi-scale coupling model into the image segmentation model based on SimVascular, and acquiring the three-dimensional grid file and the one-dimensional data file of the multi-scale coupling model through the image segmentation model;

[0069] The blood flow calculation module 44 is used to input the three-dimensional grid file and the first-dimensional data file into the solver for calculation to obtain the blood flow parameter information of the target area.

[0070] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0071] The device provided in the embodiment of the present application can be applied in the aforementioned method embodiment. For details, please refer to the description of the aforementioned method embodiment, which will not be repeated here.

[0072] See also Figure 5 , is a schematic diagram of the computer device structure of an embodiment of the present application. The computer device 50 includes:

[0073] A memory 51 storing executable program instructions;

[0074] A processor 52 connected to the memory 51;

[0075] The processor 52 is used to call the executable program instructions stored in the memory 51 and perform the following steps: obtain medical tomography image data of the target area, and construct a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data; use an optimized model coupling algorithm to perform model coupling on the three-dimensional model and the one-dimensional model to generate a multi-scale coupling model; import the multi-scale coupling model into an image segmentation model based on SimVascular, and obtain a three-dimensional grid file and a one-dimensional data file of the multi-scale coupling model through the image segmentation model; input the three-dimensional grid file and the first-dimensional data file into the solver for calculation to obtain blood flow parameter information of the target area.

[0076] The processor 52 may also be referred to as a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip having signal processing capabilities. The processor 52 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0077] See also Figure 6 , which is a schematic diagram of the structure of the storage medium of the embodiment of the present application. The storage medium of the embodiment of the present application stores program instructions 61 that can implement the following steps: obtaining medical tomography image data of the target area, and constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data; using an optimized model coupling algorithm to perform model coupling on the three-dimensional model and the one-dimensional model to generate a multi-scale coupling model; importing the multi-scale coupling model into an image segmentation model based on SimVascular, and obtaining a three-dimensional grid file and a one-dimensional data file of the multi-scale coupling model through the image segmentation model; inputting the three-dimensional grid file and the first-dimensional data file into the solver for calculation to obtain blood flow parameter information of the target area.

[0078] Among them, the program instruction 61 can be stored in the above-mentioned storage medium in the form of a software product, including several instructions for a computer device (which can be a personal computer, a server, or a network computer device, etc.) or a processor (processor) to execute all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), disk or optical disk and other media that can store program instructions, or terminal computer devices such as computers, servers, mobile phones, tablets, etc. Among them, the server can be an independent server, or it can be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0079] 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. For example, the system embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as 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 an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0080] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. The above is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the description and drawings of this application, or directly or indirectly used in other related technical fields, is also included in the patent protection scope of the present application.

Claims

1. A blood flow numerical simulation method, characterized in that: include: Acquire medical tomography image data of a target area, and construct a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data; The three-dimensional model and the one-dimensional model are coupled by using an optimized model coupling algorithm to generate a multi-scale coupling model; Importing the multi-scale coupling model into the image segmentation model based on SimVascular, and obtaining a three-dimensional grid file and a one-dimensional data file of the multi-scale coupling model through the image segmentation model; The three-dimensional grid file and the first-dimensional data file are input into a solver for calculation to obtain blood flow parameter information of the target area.

2. The blood flow numerical simulation method according to claim 1, characterized in that: The step of acquiring medical tomography image data of the target area and constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data comprises: Perform CT angiography on the target area to obtain CT image data, and reconstruct a three-dimensional model of the target area based on the CT image data.

3. The blood flow numerical simulation method according to claim 2, characterized in that: The step of acquiring medical tomography image data of the target area and constructing a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data further includes: The reconstructed three-dimensional model is geometrically processed using a geometric processing algorithm to generate a corresponding one-dimensional model.

4. The blood flow numerical simulation method according to claim 3, characterized in that: The geometric processing algorithm is used to perform geometric processing on the reconstructed three-dimensional model to generate a corresponding one-dimensional model, specifically: The thinner blood vessels in the three-dimensional model are segmented and their center lines are extracted, and a corresponding one-dimensional model is generated according to the center lines; wherein the description equation of the one-dimensional model is: Among them, Ω 1d represents the one-dimensional blood vessel area, time t∈(0,T], z represents the axial coordinate along the blood vessel, Q, P and A represent the flow, pressure and blood vessel cross-sectional area of ​​the one-dimensional model respectively, represents the time derivative of a variable, represents the derivative of the variable with respect to the axial coordinate, ρ represents the blood flow density, δ represents a parameter related to the velocity profile function on the cross section, and N represents a viscous loss term.

5. The blood flow numerical simulation method according to claim 4, characterized in that: The optimized model coupling algorithm is used to couple the three-dimensional model and the one-dimensional model to generate a multi-scale coupling model, specifically: The three-dimensional model is directly coupled with the one-dimensional model under the three-dimensional rigid wall condition, and the following equation is satisfied at the model coupling: in, represents the flow velocity in the three-dimensional model, σ represents the stress tensor in the three-dimensional model, is Γ out The normal vector of .

6. The blood flow numerical simulation method according to any one of claims 1 to 5, characterized in that: The multi-scale coupling model is imported into the image segmentation model based on SimVascular, and the three-dimensional grid file and one-dimensional data file of the multi-scale coupling model are obtained through the image segmentation model, specifically: After the multi-scale coupling model is imported into the image segmentation model based on SimVascular, the image segmentation model uses the "Models" module of SimVascular to perform three-dimensional finite element meshing on the three-dimensional model in the multi-scale coupling model, generates and exports the corresponding three-dimensional mesh file, extracts the center line of the one-dimensional model in the multi-scale coupling model, sets the one-dimensional finite element mesh unit size, generates and exports a one-dimensional data file including the finite element data coordinates of the center line and bifurcation structure information.

7. The blood flow numerical simulation method according to claim 6, characterized in that: The three-dimensional grid file and the first-dimensional data file are input into the solver for calculation to obtain the blood flow parameter information of the target area, specifically: The three-dimensional grid file and the first-dimensional data file are input into the svFSIplus_cpl 1D solver, and the three-dimensional model is parallelly calculated by the svFSIplus_cpl 1D solver to obtain the blood flow parameter information of the target area; wherein the blood flow parameter information includes pressure, flow and wall shear stress.

8. A blood flow numerical simulation device, characterized in that: include: Model building module: used for acquiring medical tomography image data of a target area, and building a three-dimensional model and a one-dimensional model of the target area according to the medical tomography image data; Model coupling module: used for coupling the three-dimensional model and the one-dimensional model using an optimized model coupling algorithm to generate a multi-scale coupling model; File acquisition module: used for importing the multi-scale coupling model into the image segmentation model based on SimVascular, and obtaining the three-dimensional grid file and one-dimensional data file of the multi-scale coupling model through the image segmentation model; Blood flow calculation module: used for inputting the three-dimensional grid file and the first-dimensional data file into the solver for calculation to obtain the blood flow parameter information of the target area.

9. A computer device, characterized in that: The computer device includes a processor and a memory coupled to the processor, wherein: The memory stores program instructions for implementing the blood flow numerical simulation method according to any one of claims 1 to 7; The processor is used to execute the program instructions stored in the memory to control the blood flow numerical simulation method.

10. A storage medium, characterized in that: Program instructions executable by a processor are stored, and the program instructions are used to execute the blood flow numerical simulation method according to any one of claims 1 to 7.

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