WO2021109116A1 - 用于流体力学分析的圆台血管数学模型的合成方法和装置 - Google Patents

用于流体力学分析的圆台血管数学模型的合成方法和装置 Download PDF

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Publication number
WO2021109116A1
WO2021109116A1 PCT/CN2019/123615 CN2019123615W WO2021109116A1 WO 2021109116 A1 WO2021109116 A1 WO 2021109116A1 CN 2019123615 W CN2019123615 W CN 2019123615W WO 2021109116 A1 WO2021109116 A1 WO 2021109116A1
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blood vessel
model
dimensional
point
truncated
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PCT/CN2019/123615
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English (en)
French (fr)
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王之元
刘广志
徐磊
王鹏
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苏州润迈德医疗科技有限公司
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/10Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/30Polynomial surface description
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/11Region-based segmentation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • G06T7/66Analysis of geometric attributes of image moments or centre of gravity
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10081Computed x-ray tomography [CT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10116X-ray image
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30101Blood vessel; Artery; Vein; Vascular

Definitions

  • the present invention relates to the technical field of coronary artery medicine, in particular to a method, device and system for synthesizing a truncated blood vessel mathematical model used for fluid mechanics analysis.
  • lipids and carbohydrates in human blood on the vascular wall will form plaques on the vascular wall, which will then cause vascular stenosis; especially the vascular stenosis that occurs near the coronary artery of the heart will cause insufficient blood supply to the myocardium and induce coronary heart disease Diseases such as angina pectoris and angina pectoris pose a serious threat to human health.
  • coronary heart disease Diseases such as angina pectoris and angina pectoris pose a serious threat to human health.
  • FFR is a kind of coronary vascular evaluation parameters
  • microcirculation resistance index IMR is a coronary vascular evaluation parameter.
  • the invention provides a method, a device and a system for synthesizing a truncated blood vessel mathematical model for fluid mechanics analysis, so as to solve the problem that there is no blood vessel mathematical model for fluid mechanics analysis in the prior art.
  • the present application provides a method for synthesizing a mathematical model of a truncated blood vessel for fluid dynamic analysis, including:
  • N-sided meshing is performed along the circumferential surface of the three-dimensional blood vessel model to form a single-layer mesh model, where N ⁇ 6;
  • the single-layer mesh model is subjected to surface layering processing to form a double-layer mesh model, that is, a mathematical model of the truncated blood vessel.
  • the N-sided meshing is performed along the circumferential surface of the three-dimensional blood vessel model to form a single-layer mesh model, where N ⁇ 6 methods include:
  • every combination of N triangles is converted into an N-sided shape to form an initial N-sided grid
  • the method of meshing along the circumference of the three-dimensional blood vessel model with triangles as the smallest unit includes:
  • the triangle as the smallest unit is an isosceles triangle.
  • the above-mentioned method for synthesizing a mathematical model of a truncated blood vessel for fluid mechanics analysis, wherein the single-layer mesh model is subjected to surface layering processing to form a double-layer mesh model that is, a method of a blood vessel mathematical model include:
  • N-sided meshing is performed along the circumferential surface of the circular truncated three-dimensional model to form another single-layer mesh model;
  • Two layers of the single-layer mesh model and the blood vessel wall thickness h form the double-layer mesh model, that is, the blood vessel mathematical model.
  • the method of performing three-dimensional modeling according to the real-time diameter D t of the blood vessel and the length L of the center line of the blood vessel to form a three-dimensional blood vessel model includes:
  • the above-mentioned method for synthesizing the mathematical model of the truncated blood vessel for fluid mechanics analysis, the real-time diameter D t of the blood vessel is obtained according to the two-dimensional angiographic image of the coronary artery, and the length L of the straightened blood vessel center line Methods include:
  • a blood vessel centerline is extracted from the two-dimensional angiographic images of the coronary arteries in each position;
  • the geometric information of the straightened blood vessel including: the real-time diameter of the blood vessel D t , and the straightened length of the blood vessel center line, that is, the center straight line length L.
  • the method of forming a three-dimensional model of the truncated cone according to the D t and L three-dimensional modeling includes:
  • the above-mentioned method for synthesizing the mathematical model of the truncated blood vessel for fluid mechanics analysis after said acquiring two-dimensional coronary angiography images of at least two positions, according to said two-dimensional coronary angiography images, real-time vessel prior to obtaining the diameter D of the length L T acquired following vascular diameter D from the starting end of the vessel and the end diameter D, and the centerline of the vessel straightened further comprising:
  • the partial blood vessel area map corresponding to the start point and the end point is segmented from the two-dimensional coronary angiography image.
  • the method for synthesizing the mathematical model of the truncated blood vessel for fluid mechanics analysis also include:
  • one piece is extracted from the two-dimensional coronary angiography image of each body position along the direction from the entrance of the coronary artery to the end of the coronary artery
  • Methods of vascular centerline include:
  • One of the blood vessel path lines is selected as the blood vessel center line.
  • the rough blood vessel diagram is meshed, and at least one blood vessel is extracted along the direction from the starting point to the ending point.
  • Ways to route the line include:
  • n is a positive integer greater than or equal to 1;
  • a line connecting the blood vessel extending direction from the starting point to the ending point is used to obtain at least one blood vessel path line.
  • the method of selecting one of the blood vessel path lines as the blood vessel centerline includes:
  • the blood vessel path line with the least amount of time is taken as the blood vessel center line.
  • the center of the blood vessel is extracted from the two-dimensional coronary angiography image of each body position along the direction from the entrance of the coronary artery to the end of the coronary artery.
  • Line methods include:
  • the method for extracting the centerline of the blood vessel from the blood vessel skeleton includes:
  • the blood vessel skeleton is searched according to the RGB values, and the point where the minimum value of the RGB difference between the starting point and the intersection on the surrounding m grids is located As the second point, search for the point where the minimum value of the RGB difference between the second point and the surrounding m grids is located as the third point, and the third point repeats the above steps until Reach the end point, where m is a positive integer greater than or equal to 1;
  • connection select one connection as the centerline of the blood vessel.
  • the above-mentioned method for synthesizing a mathematical model of a truncated blood vessel for fluid mechanics analysis the method for obtaining a straightened blood vessel contour line based on the straightened blood vessel centerline and the straightened blood vessel image include:
  • Step by step the preset contour line of the blood vessel is moved closer to the center line of the blood vessel to obtain the straightened blood vessel contour line.
  • this application provides a device for synthesizing a blood vessel mathematical model, including: a three-dimensional blood vessel model structure, a single-layer grid model structure, and a blood vessel mathematical model structure connected in sequence, the blood vessel mathematical model structure and the blood vessel mathematical model structure Three-dimensional model structure connection;
  • the three-dimensional blood vessel model structure is used to perform three-dimensional modeling according to the real-time diameter D t of the blood vessel and the length L of the blood vessel center line to form a three-dimensional blood vessel model;
  • the single-layer mesh model structure is used to perform N-sided mesh division along the circumferential surface of the three-dimensional blood vessel model to form a single-layer mesh model, where N ⁇ 6;
  • the blood vessel mathematical model structure is used to perform surface layering processing on the single-layer mesh model to form a double-layer mesh model, that is, the blood vessel mathematical model.
  • the present application provides a coronary artery analysis system, including: the above-mentioned apparatus for synthesizing a mathematical model of blood vessels.
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the method for synthesizing the mathematical model of the truncated blood vessel for fluid mechanics analysis is realized.
  • This application provides a method for synthesizing a truncated blood vessel mathematical model for fluid mechanics analysis, which solves the problem that there is no blood vessel mathematical model for fluid mechanics analysis in the prior art, and fills a gap in the industry. Since the blood vessel wall has a certain thickness, and the stenosis problem mainly occurs on the inner wall of the blood vessel, this application will build a double-layer mesh model of the blood vessel by the mathematical model of the blood vessel, which has a certain thickness. The flow velocity plays a corrective role, and the outer mesh model will fix the shape of the inner mesh model. Combined with mechanical analysis, it can effectively alleviate the deformation of the inner wall of the blood vessel, which is closer to the real blood vessel stenosis.
  • the minimum unit of the single-layer mesh model is set to a polygon with sides ⁇ 6. Due to the poor deformability of the triangle, when one side is impacted by an external force, the other side will also be deformed, resulting in greater deformation of the triangle. When the hexagon is impacted by an external force, only two sides will be deformed, and the remaining 4 sides will not be deformed. Therefore, the deformation of the hexagon is small, and the double-layer mesh model will form a hexagonal prism.
  • the hexagonal prism is more stable than the triangular prism, and compared with the triangle, the hexagon has the advantages of fewer sampling points and higher sampling efficiency. On the basis of maintaining the original blood vessel shape, it can effectively improve the calculation time of fluid mechanics analysis CFD It is the calculation efficiency, which greatly shortens the calculation time.
  • Fig. 1 is a schematic structural diagram of a truncated blood vessel mathematical model used for fluid mechanics analysis of this application;
  • FIG. 2 is a flowchart of a method for synthesizing a mathematical model of a truncated blood vessel for fluid mechanics analysis in this application;
  • Figure 3 is a schematic diagram of the structure of the single-layer grid model of this application.
  • FIG. 4 is a flowchart of S02 of the application.
  • FIG. 5 is a flowchart of S03 of this application.
  • FIG. 6 is a flowchart of S01 of the application.
  • Fig. 7 is a flowchart of S400 of this application.
  • Fig. 8 is a flowchart of S500 of the application.
  • FIG. 9 is a flowchart of the first method of S510 of this application.
  • FIG. 10 is a flowchart of S520 of the application.
  • FIG. 11 is a flowchart of the second method of S510 of this application.
  • FIG. 12 is a flowchart of S530' of the application.
  • FIG. 13 is a flowchart of S600 of this application.
  • FIG. 14 is a flowchart of S700 of the application.
  • FIG. 15 is a flowchart of S730 of this application.
  • FIG. 16 is a flowchart of S900 of this application.
  • Figure 17 is a three-dimensional blood vessel model
  • Figure 18 is a block diagram of a device for synthesizing a mathematical model of a truncated blood vessel
  • Figure 19 is a structural block diagram of a single-layer grid model structure
  • 20 is a structural block diagram of an embodiment of the three-dimensional blood vessel model structure 1 of this application;
  • FIG. 21 is another structural block diagram of an embodiment of the three-dimensional blood vessel model structure 1 of this application.
  • the present application provides a method for synthesizing a mathematical model of a truncated blood vessel for fluid mechanics analysis, including:
  • S01 Perform three-dimensional modeling according to the real-time diameter D t of the blood vessel and the length L of the blood vessel center line to form a three-dimensional blood vessel model;
  • S02 Perform N-sided mesh division along the circumferential surface of the three-dimensional blood vessel model to form a single-layer mesh model as shown in FIG. 3, where N ⁇ 6;
  • S03 Perform surface layering processing on the single-layer mesh model to form a double-layer mesh model, that is, the blood vessel mathematical model as shown in FIG. 1.
  • This application provides a method for synthesizing the mathematical model of the truncated blood vessel for fluid mechanics analysis, which solves the problem that there is no blood vessel three-dimensional mesh model for fluid mechanics analysis in the prior art, and fills the gap in the industry. Since the blood vessel wall has a certain thickness and the stenosis problem mainly occurs on the inner wall of the blood vessel, this application will build a double-layer mesh model of the blood vessel mathematical model, which is closer to the real state of the blood vessel, and the outer mesh model will The inner mesh model plays the role of shape fixation, combined with mechanical analysis can effectively alleviate the deformation of the inner wall of the blood vessel, which is closer to the real blood vessel stenosis.
  • the minimum unit of the single-layer mesh model is set to a polygon with sides ⁇ 6. Due to the poor deformability of the triangle, when one side is impacted by an external force, the other side will also be deformed, resulting in greater deformation of the triangle. When the hexagon is impacted by an external force, only two sides will be deformed, and the remaining 4 sides will not be deformed. Therefore, the deformation of the hexagon is small, and the double-layer mesh model will form a hexagonal prism.
  • the hexagonal prism is more stable than the triangular prism, and compared with the triangle, the hexagon has the advantages of fewer sampling points and higher sampling efficiency. On the basis of maintaining the original blood vessel shape, it can effectively improve the calculation time of fluid mechanics analysis CFD It is the calculation efficiency, which greatly shortens the calculation time.
  • This application provides a method for synthesizing a mathematical model of a truncated blood vessel for fluid mechanics analysis, as shown in Figure 2, including:
  • S01 Perform three-dimensional modeling according to the real-time diameter D t of the blood vessel and the length L of the center line of the blood vessel to form a three-dimensional blood vessel model, as shown in Fig. 6, including:
  • S300 Pick up the start point and end point of the blood vessel segment of interest
  • S400 segmenting a local blood vessel area map corresponding to the start point and the end point from the two-dimensional coronary angiography image, as shown in FIG. 7, including:
  • S410 Pick up at least one seed point of the blood vessel segment of interest
  • S420 Separate the two-dimensional angiographic images between two adjacent points of the starting point, the seed point, and the ending point, respectively, to obtain at least two partial blood vessel area maps;
  • extracting a blood vessel centerline from the two-dimensional angiographic images of the coronary arteries in each position includes two methods:
  • the first method is:
  • S510 Extract at least one blood vessel path line from the local blood vessel area map of each body position, as shown in FIG. 9, including:
  • each local blood vessel area map take the blood vessel segment of interest as the foreground and other areas as the background, strengthen the foreground and weaken the background, to obtain a rough blood vessel map with strong contrast;
  • S514 Obtain at least one blood vessel path line from the starting point to the ending point in the blood vessel extension direction according to the search order;
  • the blood vessel path line with the least amount of time is taken as the blood vessel center line.
  • the second method is:
  • S600 acquiring a straightened blood vessel image according to the two-dimensional coronary angiography image and the blood vessel centerline, as shown in FIG. 13, includes:
  • S620 Divide the local blood vessel area map into x units along the blood vessel extension direction from the start point to the end point, where x is a positive integer;
  • S630 Correspondingly set the blood vessel center line of each unit along the blood vessel center line;
  • the correspondingly set image is a straightened blood vessel image
  • S731 Divide the preset contour line of the blood vessel into y units, where y is a positive integer;
  • S736 The smooth curve formed by sequentially connecting contour points is the blood vessel contour line
  • S800 Acquire geometric information of the straightened blood vessel, including: the real-time diameter of the blood vessel D t , and the straightened length of the blood vessel center line, that is, the straight line length L, which is specifically:
  • the methods for obtaining the real-time blood vessel diameter D t include:
  • three-dimensional model is formed round table as shown in FIG. 17;
  • S02 Perform N-sided mesh division along the circumferential surface of the three-dimensional blood vessel model to form a single-layer mesh model, where N ⁇ 6, as shown in FIG. 4, including:
  • S021 performs mesh division along the circumferential surface of the three-dimensional blood vessel model with triangles as the smallest unit, including:
  • a triangle is used as a minimum unit for mesh division, and preferably, the triangle as the minimum unit is an isosceles triangle;
  • each combination of N triangles is converted into an N-sided shape to form an initial N-sided grid
  • S03 Perform surface layering processing on the single-layer mesh model to form a double-layer mesh model, that is, a blood vessel mathematical model, as shown in FIG. 5, including:
  • S032 Perform three-dimensional modeling according to the vessel wall thickness h, the vessel starting diameter D, the vessel ending diameter D , and the vessel centerline length L, and forming a truncated cone three-dimensional model on the inner or outer surface of the single-layer mesh model ;
  • S033 According to the method for obtaining the single-layer mesh model, perform N-sided meshing along the circumferential surface of the truncated three-dimensional model to form another single-layer mesh model;
  • the present application provides a device for synthesizing a blood vessel mathematical model, including: a three-dimensional blood vessel model structure 1, a single-layer mesh model structure 2 and a truncated vessel mathematical model structure 3 connected in sequence, the blood vessel
  • the mathematical model structure 3 is connected to the three-dimensional model structure 1; the three-dimensional blood vessel model structure 1 is used to perform three-dimensional modeling according to the real-time diameter D t of the blood vessel and the blood vessel centerline length L to form a three-dimensional blood vessel model; the single-layer grid
  • the model structure 2 is used to divide the N-sided mesh along the circumference of the three-dimensional blood vessel model to form a single-layer mesh model, where N ⁇ 6; the blood vessel mathematical model structure 3 is used to divide the single-layer mesh
  • the grid model undergoes surface stratification processing to form a double-layer grid model, that is, a mathematical model of blood vessels.
  • the three-dimensional blood vessel model structure 1 further includes: a centerline extraction unit 100, a straightening unit 200, a contour line unit 300, a geometric information unit 400, and a three-dimensional modeling unit 500 connected in sequence; the straightening unit 200 and the geometry The information unit 400 is connected, and the three-dimensional modeling unit 500 is connected to the straightening unit 200 and the contour line unit 300; the centerline extraction unit 100 is used to follow the direction of the coronary artery entrance to the end of the coronary artery, from at least two positions of the coronary arteries in two dimensions A blood vessel center line is extracted from the angiographic image; the straightening unit 200 is used to receive the blood vessel center line sent by the center line extraction unit 100, and obtain the straightened blood vessel image according to the coronary two-dimensional angiography image and the blood vessel center line; the contour line unit 300 is used After receiving the straightened blood vessel image sent by the straightening unit 200, the straightened blood vessel contour line is obtained according to the straightened blood vessel center line and the
  • the above-mentioned device further includes: an image segmentation unit 600 connected to the centerline extraction unit 100; and the image segmentation unit 600 is used to segment the coronary artery two-dimensional angiography image.
  • the local blood vessel area map corresponding to the start point and the end point, or the two-dimensional contrast image between two adjacent points of the start point, the seed point, and the end point are segmented to obtain at least two local blood vessel area maps.
  • the centerline extraction unit 100 further includes: a blood vessel path module 110 and a blood vessel centerline extraction module 120 that are connected in sequence, and the blood vessel path module 110 is connected to the image segmentation unit 600; and the blood vessel path The module 110 is used to extract at least one blood vessel path line from the local blood vessel area map of each body position; the blood vessel center line extraction module 120 is used to select one of the blood vessel path lines sent by the blood vessel path module 110 as the blood vessel center line.
  • the single-layer mesh model structure 2 further includes: a triangular mesh division unit 21, an N-sided mesh division unit 22, and a single-layer mesh model unit 23 that are sequentially connected.
  • the single-layer mesh model unit 23 is connected to the blood vessel mathematical model structure 3;
  • the triangular mesh dividing unit 21 is connected to the three-dimensional modeling unit 500, and the triangular mesh dividing unit is used to form triangles along the circumference of the three-dimensional blood vessel model.
  • the N-sided mesh division unit 22 is used to sequentially convert every N triangle combination into an N-sided shape to form an N-sided initial mesh;
  • a single-layer mesh model unit 23 It is used to delete the connecting lines inside each N-sided shape in the initial N-sided shape grid to form a single-layer N-sided shape grid model, where N ⁇ 6.
  • the present application provides a coronary artery analysis system, including: the above-mentioned device for synthesizing a mathematical model of a blood vessel.
  • This application provides a computer storage medium, and when the computer program is executed by a processor, the method for synthesizing the above-mentioned truncated blood vessel mathematical model for fluid dynamic analysis is realized.
  • aspects of the present invention can be implemented as a system, a method, or a computer program product. Therefore, various aspects of the present invention can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, resident software, microcode, etc.), or a combination of hardware and software implementations, Here can be collectively referred to as "circuit", "module” or "system”.
  • various aspects of the present invention may also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.
  • the implementation of the method and/or system of the embodiments of the present invention may involve performing or completing selected tasks manually, automatically, or in a combination thereof.
  • a data processor such as a computing platform for executing a plurality of instructions.
  • the data processor includes a volatile memory for storing instructions and/or data and/or a non-volatile memory for storing instructions and/or data, for example, a magnetic hard disk and/or a Move the media.
  • a network connection is also provided.
  • a display and/or user input device such as a keyboard or mouse, is also provided.
  • the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or a combination of any of the above. More specific examples (non-exhaustive list) of computer-readable storage media would include the following:
  • the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.
  • the computer-readable signal medium may include a data signal propagated in baseband or as a part of a carrier wave, and computer-readable program code is carried therein. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium may send, propagate, or transmit the program for use by or in combination with the instruction execution system, apparatus, or device .
  • the program code contained on the computer-readable medium can be transmitted by any suitable medium, including (but not limited to) wireless, wired, optical cable, RF, etc., or any suitable combination of the above.
  • any combination of one or more programming languages can be used to write computer program codes for performing operations for various aspects of the present invention, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional process programming languages, such as "C" programming language or similar programming language.
  • the program code can be executed entirely on the user's computer, partly on the user's computer, executed as an independent software package, partly on the user's computer and partly executed on a remote computer, or entirely executed on the remote computer or server.
  • the remote computer can be connected to the user's computer through any kind of network-including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to pass Internet connection).
  • LAN local area network
  • WAN wide area network
  • each block of the flowchart and/or block diagram and the combination of each block in the flowchart and/or block diagram can be implemented by computer program instructions.
  • These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine that makes these computer program instructions when executed by the processor of the computer or other programmable data processing device , A device that implements the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams is produced.
  • These computer program instructions can also be stored in a computer-readable medium. These instructions make computers, other programmable data processing devices, or other devices work in a specific manner, so that the instructions stored in the computer-readable medium generate An article of manufacture that implements instructions for the functions/actions specified in one or more blocks in the flowchart and/or block diagram.
  • Computer program instructions can also be loaded onto a computer (for example, a coronary artery analysis system) or other programmable data processing equipment to cause a series of operation steps to be executed on the computer, other programmable data processing equipment or other equipment to produce a computer-implemented process , Causing instructions executed on a computer, other programmable device or other equipment to provide a process for implementing the functions/actions specified in the flowchart and/or one or more block diagrams.
  • a computer for example, a coronary artery analysis system
  • other programmable data processing equipment or other equipment to produce a computer-implemented process
  • Causing instructions executed on a computer, other programmable device or other equipment to provide a process for implementing the functions/actions specified in the flowchart and/or one or more block diagrams.

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Abstract

一种用于流体力学分析的圆台血管数学模型的合成方法和装置,包括:根据血管实时直径Dt、血管中心线长度L进行三维建模,形成三维血管模型(S01);沿着三维血管模型的圆周面进行N边型网格划分,形成单层网格模型(S02);对单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型(S03)。该方法和装置解决了现有技术中没有用于流体力学分析的血管三维网格模型的问题,弥补了行业的空白;由于血管壁具有一定的厚度,且主要在血管内壁会出现狭窄问题,因此通过将血管数学模型建成双层网格模型,具有一定的厚度,内层网格模型具有弹性,能够对血流速度起到修正作用,更加接近于血管的真实状态。

Description

用于流体力学分析的圆台血管数学模型的合成方法和装置 技术领域
本发明涉及冠状动脉医学技术领域,特别是涉及一种用于流体力学分析的圆台血管数学模型的合成方法、装置及系统。
背景技术
人体血液中的脂类及糖类物质在血管壁上的沉积将在血管壁上形成斑块,继而导致血管狭窄;特别是发生在心脏冠脉附近的血管狭窄将导致心肌供血不足,诱发冠心病、心绞痛等病症,对人类的健康造成严重威胁。据统计,我国现有冠心病患者约1100万人,心血管介入手术治疗患者数量每年增长大于10%。
冠脉造影CAG、计算机断层扫描CT等常规医用检测手段虽然可以显示心脏冠脉血管狭窄的严重程度,但是并不能准确评价冠脉的缺血情况。为提高冠脉血管功能评价的准确性,1993年Pijls提出了通过压力测定推算冠脉血管功能的新指标——血流储备分数(Fractional Flow Reserve,FFR),经过长期的基础与临床研究,FFR已成为冠脉狭窄功能性评价的金标准。
FFR是冠状动脉血管评定参数的一种,微循环阻力指数IMR等属于冠状动脉血管评定参数。
在冠状动脉造影图像中,需要结合流体力学分析CFD计算冠状动脉血管评定参数,而现有技术中没有用于流体力学分析的血管数学模型。
发明内容
本发明提供了一种用于流体力学分析的圆台血管数学模型的合成方法、装置及系统,以解决现有技术中没有用于流体力学分析的血管数学模型的问题。
为实现上述目的,第一方面,本申请提供了一种用于流体力学分析的圆台血管数学模型的合成方法,包括:
根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;
沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6;
对所述单层网格模型进行表面分层化处理,形成双层网格模型,即圆台血管数学模型。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6的方法包括:
沿着所述三维血管模型的圆周面,以三角形为最小单元进行网格划分;
按照顺序,每N个三角形组合转换成1个N边形,形成N边形初始网格;
删除所述N边形初始网格中每个N边形内部的连接线,形成单层N边形网格模型,其中N≥6。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述沿着所述三维血管模型的圆周面,以三角形为最小单元进行网格划分的方法包括:
将所述三维血管模型分割成K段,
在每分段所述三维血管模型的圆周面上,以三角形为最小单元进行网格划分。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,作为最小单元的所述三角形为等腰三角形。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型的方法包括:
获取血管壁厚h;
根据所述血管壁厚h、血管起始直径D 、血管结束直径D 和血管中心线长度L进行三维建模,在所述单层网格模型内表面或者外表面形成圆台三维模型;
根据所述单层网格模型的获取方法,沿着所述圆台三维模型的圆周面进行N边型网格划分,形成另一单层网格模型;
两层所述单层网格模型与所述血管壁厚h,形成所述双层网格模型,即所述血管数学模型。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型的方法包括:
获取至少两个体位的冠状动脉二维造影图像;
根据所述冠状动脉二维造影图像,获得血管实时直径D t,以及血管中心线拉直后的长度L;
根据所述D t和L三维建模,形成圆台三维模型。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述根据所述冠状动脉二维造影图像,获得血管实时直径D t,以及血管中心线拉直后的长度L的方法包括:
沿着冠脉入口至冠脉末端方向,从每个体位的所述冠状动脉二维造影图像中均提取一条血管中心线;
根据所述冠状动脉二维造影图像和所述血管中心线获取拉直血管图像;
根据拉直后的所述血管中心线和所述拉直血管图像,获取拉直后的血管轮廓线;
获取拉直后的血管的几何信息,包括:血管实时直径D t,及血管中心线拉直后的长度即中心直线长度L。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述根据所述D t和L三维建模,形成圆台三维模型的方法包括:
根据所述几何信息、所述中心线和所述轮廓线进行三维建模,获得三维血管模型;
从所述血管实时直径D t内获取血管起始直径D 和血管结束直径D
根据所述D 、D 和L进行三维建模,形成所述圆台三维模型。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,在所述获取至少两个体位的冠状动脉二维造影图像之后,在所述根据所述冠状动脉二维造影图像,获得血管实时直径D t内获取血管起始直径D 和血管结束直径D ,以及血管中心线拉直后的长度L之前还包括:
从所述冠状动脉二维造影图像中获取感兴趣的血管段;
拾取所述感兴趣的血管段的起始点和结束点;
从所述冠状动脉二维造影图像中分割出所述起始点、结束点对应的局部血管区域图。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述从所述冠状动脉二维造影图像中分割出所述起始点、结束点对应的局部血管区域图的方法还包括:
拾取所述感兴趣的血管段的至少一个种子点;
分别对起始点、种子点、结束点的相邻两点间的二维造影图像进行分割,得到至少两个局部血管区域图。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述沿着冠脉入口至冠脉末端方向,从每个体位的所述冠状动脉二维造影图像中均提取一条血管中心线的方法包括:
对所述局部血管区域图做图像增强处理,得到对比强烈的粗略血管图;
对所述粗略血管图做网格划分,沿着所述起始点至所述结束点方向,提取至少一条血管路径线;
选取一条所述血管路径线作为所述血管中心线。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述对所述粗略血管图做网格划分,沿着所述起始点至所述结束点方向,提取至少一条血管路径线的方法包括:
对所述粗略血管图进行网格划分;
沿着所述起始点至所述结束点的血管延伸方向,搜索所述起始点与周边n个网格上的交叉点的最短时间路径作为第二个点,搜索所述第二个点与周边n个网格上的交叉点的最短时间路径作为第三个点,所述第三个点重复上述步骤,直至最短时间路径到达结束点,其中,n为大于等于1的正整数;
按照搜索顺序,从所述起始点至所述结束点的血管延伸方向连线,获得至少一条血管路径线。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述选取一条所述血管路径线作为所述血管中心线的方法包括:
如果血管路径线为两条或两条以上,则对每条血管路径线从所述起始点至所述结束点所用的时间求和;
取用时最少的所述血管路径线作为所述血管中心线。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述沿着冠脉入口至冠脉末端方向,从每个体位的冠状动脉二维造影图像中均提取一条血管中心线的方法包括:
对所述局部血管区域图进行图像处理,获取所述起始点和所述结束点之间的血管粗略走向线;
获取血管粗略边缘线,包含有所述血管粗略走向线的所述血管粗略边缘线之间的图像即为血管骨架;
从所述血管骨架上提取所述血管中心线。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述从所述血管骨架上提取所述血管中心线的方法包括:
对处理后的所述区域图像进行网格划分;
沿着所述起始点至所述结束点方向,根据RGB值,对所述血管骨架进行搜索,搜索所述起始点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第二个点,搜索所述第二个点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第三个点,所述第三个点重复上述步骤,直至到达结束点,其中,m为大于等于1的正整数;
按照搜索顺序,从所述起始点至所述结束点获得至少一条连线;
如果连线为两条或两条以上,选取一条连线作为所述血管中心线。
可选地,上述的用于流体力学分析的圆台血管数学模型的合成方法,所述根据拉直后的所述血管中心线和所述拉直血管图像,获取拉直后的血管轮廓线的方法包括:
在所述拉直血管图像上,设定血管直径阈值D
根据所述D ,在所述血管中心直线两侧生成血管预设轮廓线;
将所述血管预设轮廓线向所述血管中心直线逐级靠拢,获取拉直后的血管轮廓线。
第二方面,本申请提供了一种用于合成血管数学模型的装置,包括:依次连接的三维血管模型结构、单层网格模型结构和血管数学模型结构,所述血管数学模型结构与所述三维模型结构连接;
所述三维血管模型结构,用于根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;
所述单层网格模型结构,用于沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6;
所述血管数学模型结构,用于对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型。
第三方面,本申请提供了一种冠状动脉分析系统,包括:上述的用于合成血管数学模型的装置。
第四方面,本申请提供了一种计算机存储介质,计算机程序被处理器执行时实现上述的用于流体力学分析的圆台血管数学模型的合成方法。
本申请实施例提供的方案带来的有益效果至少包括:
本申请提供了用于流体力学分析的圆台血管数学模型的合成方法,解决了现有技术中没有用于流体力学分析的血管数学模型的问题,弥补了行业的空白。由于血管壁具有一定的厚度,且主要在血管内壁会出现狭窄问题,因此本申请将通过将血管数学模型建成双层网格模型,具有一定的厚度,内层网格模型具有弹性,能够对血流速度起到修正作用,且外层网格模型会对内层网格模型起到形状固定的作用,结合力学分析能够有效的缓解血管内壁的变形,更加接近于真实血管狭窄的情况。进一步地,将单层网格模型的最小单元设置成边数≥6的多边形,由于三角形的形变能力较差,在一条边受到外力冲击时,另一条边也会发生形变,导致三角形的形变较大,而六边形在受到外力冲击时,只有两条边发生形变,其余4条边不会发生形变,因此六边形的形变较小,且双层网格模型会形成六边形棱柱,六边形棱柱相对于三角形棱柱更加稳定,且六边形相对于三角形具有采样点数量较少和采样效率较高等优势,在保持原有血管形态的基础上,能有效的提高流体力学分析CFD计算时的是计算效率,极大缩短计算时间。
附图说明
此处所说明的附图用来提供对本发明的进一步理解,构成本发明的一部分,本发明的示意性实施例及其说明用于解释本发明,并不构成对本发明的不当限定。在附图中:
图1为本申请的用于流体力学分析的圆台血管数学模型的结构示意图;
图2为本申请的用于流体力学分析的圆台血管数学模型的合成方法的流程图;
图3为本申请的单层网格模型的结构示意图;
图4为本申请的S02的流程图;
图5为本申请的S03的流程图;
图6为本申请的S01的流程图;
图7为本申请的S400的流程图;
图8为本申请的S500的流程图;
图9为本申请的S510的第一种方法的流程图;
图10为本申请的S520的流程图;
图11为本申请的S510的第二种方法的流程图;
图12为本申请的S530’的流程图;
图13为本申请的S600的流程图;
图14为本申请的S700的流程图;
图15为本申请的S730的流程图;
图16为本申请的S900的流程图;
图17为三维血管模型;
图18为用于合成圆台血管数学模型的装置的结构框图;
图19为单层网格模型结构的结构框图;
图20为本申请的三维血管模型结构1的一个实施例的结构框图;
图21为本申请的三维血管模型结构1的一个实施例的另一结构框图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚,下面将结合本发明具体实施例及相应的附图对本发明技术方案进行清楚、完整地描述。显然,所描述的实施例仅是本发明一部分实施例,而不是全部的实施例。基于本发明中的实施例,本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例,都属于本发明保护的范围。
以下将以图式揭露本发明的多个实施方式,为明确说明起见,许多实务上的细节将在以下叙述中一并说明。然而,应了解到,这些实务上的细节不应用以限制本发明。也就是说,在本发明的部分实施方式中,这些实务上的细节是非必要的。此外,为简化图式起见,一些习知惯用的结构与组件在图式中将以简单的示意的方式绘示之。
在冠状动脉造影图像中,需要结合流体力学分析计算冠状动脉血管评定参数,而现有技术中没有用于流体力学分析的血管数学模型。
实施例1:
如图2所示,本申请提供了一种用于流体力学分析的圆台血管数学模型的合成方法,包括:
S01,根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;
S02,沿着所述三维血管模型的圆周面进行N边型网格划分,形成如图3所示的单层网格模型,其中N≥6;
S03,对所述单层网格模型进行表面分层化处理,形成双层网格模型,即如图1所示的血管数学模型。
本申请提供了用于流体力学分析的圆台血管数学模型的合成方法,解决了现有技术中没有用于流体力学分析的血管三维网格模型的问题,弥补了行业的空白。由于血管壁具有一定的厚度,且主要在血管内壁会出现狭窄问题,因此本申请将通过将血管数学模型建成双层网格模型,更加接近于血管的真实状态,且外层网格模型会对内层网格模型起到形状固定的作用,结合力学分析能够有效的缓解血管内壁的变形,更加接近于真实血管狭窄的情况。进一步地,将单层网格模型的最小单元设置成边数≥6的多边形,由于三角形的形变能力较差,在一条边受到外力冲击时,另一条边也会发生形变,导致三角形的形变较大,而六边形在受到外力冲击时,只有两条边发生形变,其余4条边不会发生形变,因此六边形的形变较小,且双层网格模型会形成六边形棱柱,六边形棱柱相对于三角形棱柱更加稳定,且六边形相对于三角形具有采样点数量较少和采样效率较高等优势,在保持原有血管形态的基础上,能有效的提高流体力学分析CFD计算时的是计算效率,极大缩短计算时间。
实施例2:
本申请提供了一种用于流体力学分析的圆台血管数学模型的合成方法,如图2所示,包括:
S01,根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型,如图6所示,包括:
S100,获取至少两个体位的冠状动脉二维造影图像;优选地,两个体位之间的夹角大于等于30度;
S200,从所述冠状动脉二维造影图像中获取感兴趣的血管段;
S300,拾取感兴趣的血管段的起始点和结束点;
S400,从冠状动脉二维造影图像中分割出起始点、结束点对应的局部血管区域图,如图7所示,包括:
S410,拾取感兴趣的血管段的至少一个种子点;
S420,分别对起始点、种子点、结束点的相邻两点间的二维造影图像进行分割,得到至少两个局部血管区域图;
S500,根据所述冠状动脉二维造影图像,获得血管实时直径D t,以及血管中心线拉直后的长度L,包括:
沿着冠脉入口至冠脉末端方向,从每个体位的所述冠状动脉二维造影图像中均提取一条血管中心线,包括两种方法:
如图8所示,第一种方法为:
S510,分别从每个体位的局部血管区域图上提取至少一条血管路径线,如图9所示,包括:
S511,在每幅局部血管区域图中,以感兴趣的血管段作为前景,其他区域作为背景,强化前景,弱化背景,得到对比强烈的粗略血管图;
S512,对粗略血管图进行网格划分;
S513,沿着起始点至结束点的血管延伸方向,搜索起始点与周边n个网格上的交叉点的最短时间路径作为第二个点,搜索第二个点与周边n个网格上的交叉点的最短时间路径作为第三个点,第三个点重复上述步骤,直至最短时间路径到达结束点,其中,n为大于等于1的正整数;
S514,按照搜索顺序,从起始点至结束点的血管延伸方向连线,获得至少一条血管路径线;
S520,选取一条血管路径线作为血管中心线,如图10所示,包括:
S521,如果血管路径线为两条或两条以上,则对每条血管路径线从起始点至结束点所用的时间求和;
S522,取用时最少的血管路径线作为血管中心线。
如图11所示,第二种方法为:
S510’,对局部血管区域图进行图像处理,获取起始点和结束点之间的血管粗略走向线;
S520’,获取血管粗略边缘线,包含有血管粗略走向线的血管粗略边缘线之间的图像即为血管骨架;
S530’,从血管骨架上提取血管中心线,如图12所示,包括:
S531’,对处理后的区域图像进行网格划分;
S532’,沿着起始点至结束点方向,根据RGB值,对血管骨架进行搜索,搜索起始点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第二个点,搜索第二个点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第三个点,第三个点重复上述步骤,直至到达结束点,其中,m为大于等于1的正整数;
S533’,按照搜索顺序,从起始点至结束点获得至少一条连线;
S534’,如果连线为两条或两条以上,选取一条连线作为血管中心线。
S600,根据所述冠状动脉二维造影图像和所述血管中心线获取拉直血管图像,如图13所示,包括:
S610,将血管中心线拉直,获得血管中心直线;
S620,沿着起始点至结束点的血管延伸方向,将局部血管区域图分为x个单元,其中x为正整数;
S630,将每个单元的血管中心线沿着血管中心直线对应设置;
S640,对应设置后的图像为拉直血管图像;
S700,根据拉直后的所述血管中心线和所述拉直血管图像,获取拉直后的血管轮廓线,如图14所示,包括:
S710,在拉直血管图像上,设定血管直径阈值D
S720,根据D ,在血管中心直线两侧生成血管预设轮廓线;
S730,将血管预设轮廓线向血管中心直线逐级靠拢,获取拉直后的血管轮廓线,如图15所示,包括:
S731,将血管预设轮廓线分成y个单元,其中y为正整数;
S732,获取每个单元的位于每条血管预设轮廓线上的z个点;
S733,沿着垂直于血管中心直线方向,将z个点分别向血管中心直线分级靠拢,产生z个靠拢点,其中z为正整数;
S734,设定RGB差值阈值为ΔRGB ,沿着垂直于血管中心直线方向,每次靠拢均将靠拢点的RGB值与血管中心直线上的点的RGB值作比较,当差值小于等于ΔRGB 时,则靠拢点停止向血管中心直线靠拢;
S735,获取靠拢点作为轮廓点;
S736,依次连接轮廓点形成的平滑曲线即为血管轮廓线;
S800,获取拉直后的血管的几何信息,包括:血管实时直径D t,及血管中心线拉直后的长度即中心直线长度L,具体为:
(1)血管实时直径D t、(2)血管中心直线长度L;
(1)血管实时直径D t的获取方法包括:
沿着垂直于血管中心直线方向,获取相对设置的所有轮廓点之间的距离,即为血管实时直径D t
S900,根据所述D t和L三维建模,形成圆台三维模型,如图16所示,包括:
S910,从所述血管实时直径D t内获取血管起始直径D 和血管结束直径D ,以及血管中心直线长度L;
S920,根据D 和D 和L三维建模,形成如图17所示的圆台三维模型;
S02,沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6,如图4所示,包括:
S021沿着所述所述三维血管模型的圆周面,以三角形为最小单元进行网格划分,包括:
将所述三维血管模型分割成K段,
在每分段所述三维血管模型的圆周面上,以三角形为最小单元进行网格划分,优选地,作为最小单元的三角形为等腰三角形;
S022,按照顺序,每N个三角形组合转换成1个N边形,形成N边形初始网格;
S023,删除所述N边形初始网格中每个N边形内部的连接线,形成单层N边形网格模型,其中N≥6;
S03,对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型,如图5所示,包括:
S031,获取血管壁厚h;优选地,h=0.2mm~2mm;
S032,根据所述血管壁厚h、血管起始直径D起、血管结束直径D 和血管中心线长度L进行三维建模,在所述单层网格模型内表面或者外表面形成圆台三维模型;
S033,根据所述单层网格模型的获取方法,沿着所述圆台三维模型的圆周面进行N边型网格划分,形成另一单层网格模型;
S034,两层所述单层网格模型与所述血管壁厚h,形成所述双层网格模型,即所述血管数学模型。
实施例3:
如图18所示,本申请提供了一种用于合成血管数学模型的装置,包括:依次连接的三维血管模型结构1、单层网格模型结构2和圆台血管数学模型结构3,所述血管数学模型结构3与所述三维模型结构1连接;所述三维血管模型结构1用于根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;所述单层网格模型结构2用于沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6;所述血管数学模型结构3用于对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型。
如图20所示,三维血管模型结构1还包括:依次连接的中心线提取单元100、拉直单元200、轮廓线单元300、几何信息单元400和三维建模单元500;拉直单元200与几何信息单元400连接,三维建模单元500与拉直单元200、轮廓线单元300连接;中心线提取单元100用于沿着冠脉入口至冠脉末端方向,从至少两个体位的冠状动脉二维造影图像中均提取一条血管中心线;拉直单元200用于接收中心线提取单元100发送的血管中心线,根据冠状动脉二维造影图像和血管中心线获取拉直血管图像;轮廓线单元300用于接收拉直单元200发送的拉直血管图像,根据拉直后的血管中心线和拉直血管图像,获取拉直后的血管轮廓线;几何信息单元400用于接收拉直单元200发送的拉直血管图像、轮廓线单元300发送的血管轮廓线,获取拉直后的血管的几何信息;三维建模单元500用于接收拉直单元200发送的拉直血管图像、轮廓线单元300发送的血管轮廓线、几何信息单元400发送的血管的几何信息,根据几何信息、中心线和轮廓线进行三维建模,获得三维血管模型。
如图21所示,本申请的一个实施例中,上述装置还包括:与中心线提取单元100连接的图像分割单元600;图像分割单元600,用于从冠状动脉二维造影图像中分割出起始点、结束点对应的局部血管区域图,或者对起始点、种子点、结束点的相邻两点间的二维造影图像进行分割,得到至少两个局部血管区域图。
如图21所示,本申请的一个实施例中,中心线提取单元100还包括:依次连接的血管路径模块110和血管中心线提取模块120,血管路径模块110与图像分割单元600连接;血管路径模块110,用于分别从每个体位的局部血管区域图上提取至少一条血管路径线;血管中心线提取模块120,用于从血管路径模块110发送的血管路径线中选取一条作为血管中心线。
如图19所示,本申请的一个实施例中,单层网格模型结构2还包括:依次连接的三角形网格划分单元21、N边形网格划分单元22和单层网格模型单元23,单层网格模型单元23与血管数学模型结构3连接;三角形网格划分单元21与三维建模单元500连接,三角形网格划分单元用于沿着所述三维血管模型的圆周面,以三角形为最小单元进行网格划分;N边形网格划分单元22用于按照顺序,将每N个三角形组合转换成1个N边形,形成N边形初始网格;单层网格模型单元23用于删除所述N边形初始网格中每个N边形内部的连接线,形成单层N边形网格模型,其中N≥6。
本申请提供了一种冠状动脉分析系统,包括:上述的用于合成血管数学模型的装置。
本申请提供了一种计算机存储介质,计算机程序被处理器执行时实现上述的用于流体力学分析的圆台血管数学模型的合成方法。
所属技术领域的技术人员知道,本发明的各个方面可以实现为系统、方法或计算机程序产品。因此,本发明的各个方面可以具体实现为以下形式,即:完全的硬件实施方式、完全的软件实施方式(包括固件、驻留软件、微代码等),或硬件和软件方面结合的实施方式,这里可以统称为“电路”、“模块”或“系统”。此外,在一些实施例中,本发明的各个方面还可以实现为在一个或多个计算机可读介质中的计算机程序产品的形式,该计算机可读介质中包含计算机可读的程序代码。本发明的实施例的方法和/或系统的实施方式可以涉及到手动地、自动地或以其组合的方式执行或完成所选任务。
例如,可以将用于执行根据本发明的实施例的所选任务的硬件实现为芯片或电路。作为软件,可以将根据本发明的实施例的所选任务实现为由计算机使用任何适当操作系统执行的多个软件指令。在本发明的示例性实施例中,由数据处理器来执行如本文的根据方法和/或系统的示例性实施例的一个或多个任务,诸如用于执行多个指令的计算平台。可选地,该数据处理器包括用于存储指令和/或数据的易失性储存器和/或用于存储指令和/或数据的非易失性储存器,例如,磁硬盘和/或可移动介质。可选地,也提供了一种网络连接。可选地也提供显示器和/或用户输入设备,诸如键盘或鼠标。
可利用一个或多个计算机可读的任何组合。计算机可读介质可以是计算机可读信号介质或计算机可读存储介质。计算机可读存储介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件,或者任意以上的组合。计算机可读存储介质的更具体的例子(非穷举列表)将包括以下各项:
具有一个或多个导线的电连接、便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本文件中,计算机可读存储介质可以是任何包含或存储程序的有形介质,该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。
计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号,其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式,包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质,该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。
计算机可读介质上包含的程序代码可以用任何适当的介质传输,包括(但不限于)无线、有线、光缆、RF等等,或者上述的任意合适的组合。
例如,可用一个或多个编程语言的任何组合来编写用于执行用于本发明的各方面的操作的计算机程序代码,包括诸如Java、Smalltalk、C++等面向对象编程语言和常规过程编程语言,诸如"C"编程语言或类似编程语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中,远程计算机可以通过任意种类的网络--包括局域网(LAN)或广域网(WAN)-连接到用户计算机,或者,可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。
应当理解,流程图和/或框图的每个方框以及流程图和/或框图中各方框的组合,都可以由计算机程序指令实现。这些计算机程序指令可以提供给通用计算机、专用计算机或其它可编程数据处理装置的处 理器,从而生产出一种机器,使得这些计算机程序指令在通过计算机或其它可编程数据处理装置的处理器执行时,产生了实现流程图和/或框图中的一个或多个方框中规定的功能/动作的装置。
也可以把这些计算机程序指令存储在计算机可读介质中,这些指令使得计算机、其它可编程数据处理装置、或其它设备以特定方式工作,从而,存储在计算机可读介质中的指令就产生出包括实现流程图和/或框图中的一个或多个方框中规定的功能/动作的指令的制造品(article of manufacture)。
还可将计算机程序指令加载到计算机(例如,冠状动脉分析系统)或其它可编程数据处理设备上以促使在计算机、其它可编程数据处理设备或其它设备上执行一系列操作步骤以产生计算机实现过程,使得在计算机、其它可编程装置或其它设备上执行的指令提供用于实现在流程图和/或一个或多个框图方框中指定的功能/动作的过程。
本发明的以上的具体实例,对本发明的目的、技术方案和有益效果进行了进一步详细说明,所应理解的是,以上仅为本发明的具体实施例而已,并不用于限制本发明,凡在本发明的精神和原则之内,所做的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。

Claims (19)

  1. 用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,包括:
    根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;
    沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6;
    对所述单层网格模型进行表面分层化处理,形成双层网格模型,即圆台血管数学模型。
  2. 根据权利要求1所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6的方法包括:
    沿着所述所述三维血管模型的圆周面,以三角形为最小单元进行网格划分;
    按照顺序,每N个三角形组合转换成1个N边形,形成N边形初始网格;
    删除所述N边形初始网格中每个N边形内部的连接线,形成单层N边形网格模型,其中N≥6。
  3. 根据权利要求2所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述沿着所述所述三维血管模型的圆周面,以三角形为最小单元进行网格划分的方法包括:
    将所述三维血管模型分割成K段,
    在每分段所述三维血管模型的圆周面上,以三角形为最小单元进行网格划分。
  4. 根据权利要求2所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,作为最小单元的所述三角形为等腰三角形。
  5. 根据权利要求1所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型的方法包括:
    获取血管壁厚h;
    根据所述血管壁厚h、血管起始直径D 、血管结束直径D 和血管中心线长度L进行三维建模,在所述单层网格模型内表面或者外表面形成圆台三维模型;
    根据所述单层网格模型的获取方法,沿着所述圆台三维模型的圆周面进行N边型网格划分,形成另一单层网格模型;
    两层所述单层网格模型与所述血管壁厚h,形成所述双层网格模型,即所述圆台血管数学模型。
  6. 根据权利要求1所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型的方法包括:
    获取至少两个体位的冠状动脉二维造影图像;
    根据所述冠状动脉二维造影图像,获得血管实时直径D t,以及血管中心线拉直后的长度L;
    根据所述D t和L三维建模,形成另一圆台三维模型,即三维血管模型。
  7. 根据权利要求6所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述根据所述冠状动脉二维造影图像,获得血管实时直径D t,以及血管中心线拉直后的长度L的方法包括:
    沿着冠脉入口至冠脉末端方向,从每个体位的所述冠状动脉二维造影图像中均提取一条血管中心线;
    根据所述冠状动脉二维造影图像和所述血管中心线获取拉直血管图像;
    根据拉直后的所述血管中心线和所述拉直血管图像,获取拉直后的血管轮廓线;
    获取拉直后的血管的几何信息,包括:血管实时直径D t,及血管中心线拉直后的长度即中心直线长度L。
  8. 根据权利要求6所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述根据所述D t和L三维建模,形成圆台三维模型的方法包括:
    根据所述几何信息、所述中心线和所述轮廓线进行三维建模,获得三维血管模型;
    从所述血管实时直径D t内获取血管起始直径D 和血管结束直径D
    根据所述D 、D 和L进行三维建模,形成所述圆台三维模型。
  9. 根据权利要求6所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,在所述获取至少两个体位的冠状动脉二维造影图像之后,在所述根据所述冠状动脉二维造影图像,获得血管实时直径D t内获取血管起始直径D 和血管结束直径D ,以及血管中心线拉直后的长度L之前还包括:
    从所述冠状动脉二维造影图像中获取感兴趣的血管段;
    拾取所述感兴趣的血管段的起始点和结束点;
    从所述冠状动脉二维造影图像中分割出所述起始点、结束点对应的局部血管区域图。
  10. 根据权利要求9所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述从所述冠状动脉二维造影图像中分割出所述起始点、结束点对应的局部血管区域图的方法还包括:
    拾取所述感兴趣的血管段的至少一个种子点;
    分别对起始点、种子点、结束点的相邻两点间的二维造影图像进行分割,得到至少两个局部血管区域图。
  11. 根据权利要求7所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述沿着冠脉入口至冠脉末端方向,从每个体位的所述冠状动脉二维造影图像中均提取一条血管中心线的方法包括:
    对所述局部血管区域图做图像增强处理,得到对比强烈的粗略血管图;
    对所述粗略血管图做网格划分,沿着所述起始点至所述结束点方向,提取至少一条血管路径线;
    选取一条所述血管路径线作为所述血管中心线。
  12. 根据权利要求11所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述对所述粗略血管图做网格划分,沿着所述起始点至所述结束点方向,提取至少一条血管路径线的方法包括:
    对所述粗略血管图进行网格划分;
    沿着所述起始点至所述结束点的血管延伸方向,搜索所述起始点与周边n个网格上的交叉点的最短时间路径作为第二个点,搜索所述第二个点与周边n个网格上的交叉点的最短时间路径作为第三个点,所述第三个点重复上述步骤,直至最短时间路径到达结束点,其中,n为大于等于1的正整数;
    按照搜索顺序,从所述起始点至所述结束点的血管延伸方向连线,获得至少一条血管路径线。
  13. 根据权利要求12所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述选取一条所述血管路径线作为所述血管中心线的方法包括:
    如果血管路径线为两条或两条以上,则对每条血管路径线从所述起始点至所述结束点所用的时间求和;
    取用时最少的所述血管路径线作为所述血管中心线。
  14. 根据权利要求7所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述沿着冠脉入口至冠脉末端方向,从每个体位的冠状动脉二维造影图像中均提取一条血管中心线的方法包 括:
    对所述局部血管区域图进行图像处理,获取所述起始点和所述结束点之间的血管粗略走向线;
    获取血管粗略边缘线,包含有所述血管粗略走向线的所述血管粗略边缘线之间的图像即为血管骨架;
    从所述血管骨架上提取所述血管中心线。
  15. 根据权利要求14所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述从所述血管骨架上提取所述血管中心线的方法包括:
    对处理后的所述区域图像进行网格划分;
    沿着所述起始点至所述结束点方向,根据RGB值,对所述血管骨架进行搜索,搜索所述起始点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第二个点,搜索所述第二个点与周边m个网格上的交叉点的RGB差值的最小值所在的点作为第三个点,所述第三个点重复上述步骤,直至到达结束点,其中,m为大于等于1的正整数;
    按照搜索顺序,从所述起始点至所述结束点获得至少一条连线;
    如果连线为两条或两条以上,选取一条连线作为所述血管中心线。
  16. 根据权利要求15所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,所述根据拉直后的所述血管中心线和所述拉直血管图像,获取拉直后的血管轮廓线的方法包括:
    在所述拉直血管图像上,设定血管直径阈值D
    根据所述D ,在所述血管中心直线两侧生成血管预设轮廓线;
    将所述血管预设轮廓线向所述血管中心直线逐级靠拢,获取拉直后的血管轮廓线。
  17. 用于合成圆台血管数学模型的装置,用于权利要求1~16任一项所述的用于流体力学分析的圆台血管数学模型的合成方法,其特征在于,包括:依次连接的三维血管模型结构、单层网格模型结构和血管数学模型结构,所述血管数学模型结构与所述三维模型结构连接;
    所述三维血管模型结构,用于根据血管实时直径D t、血管中心线长度L进行三维建模,形成三维血管模型;
    所述单层网格模型结构,用于沿着所述三维血管模型的圆周面进行N边型网格划分,形成单层网格模型,其中N≥6;
    所述血管数学模型结构,用于对所述单层网格模型进行表面分层化处理,形成双层网格模型,即血管数学模型。
  18. 一种冠状动脉分析系统,其特征在于,包括:权利要求17所述的用于合成圆台血管数学模型的装置。
  19. 一种计算机存储介质,其特征在于,计算机程序被处理器执行时实现权利要求1~16任一项所述的用于流体力学分析的圆台血管数学模型的合成方法。
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