CN106887000A

CN106887000A - The gridding processing method and its system of medical image

Info

Publication number: CN106887000A
Application number: CN201710051405.1A
Authority: CN
Inventors: 王洪建; 马杰延; 任远
Original assignee: Shanghai United Imaging Healthcare Co Ltd
Current assignee: Shanghai United Imaging Healthcare Co Ltd
Priority date: 2017-01-23
Filing date: 2017-01-23
Publication date: 2017-06-23
Anticipated expiration: 2037-01-23
Also published as: CN106887000B

Abstract

The present invention provides a kind of the gridding processing method and its system of medical image, and methods described includes：A two dimensional image is obtained, the two dimensional image includes one or more regions interested；Extract multiple profile points of one or more of area-of-interests；According to the multiple profile point, a first area and a second area are determined；Based on a first mesh generation control condition, the grid of the first area is generated；Based on a second mesh generation control condition, the grid of the second area is generated.Methods described disclosed by the invention and its system, to improve mesh quality, can meet follow-up visit demand with multiple semi-cylindrical hills grid density degree in flexible modulation medical image.

Description

The gridding processing method and its system of medical image

【Technical field】

The present invention relates to field of medical image processing, more particularly to a kind of medical image gridding processing method and its dress Put.

【Background technology】

Mess generation can be understood as generating a polygon or the approximate geometry domain of polyhedron grid.Grid is typically used Way is to be rendered into computer screen or physical analogy, such as finite element analysis or computational fluid dynamics.Mess generation is one comprehensive The problem that mathematics, engineering science, computer science, Art Theory are integrated is closed.How to generate a high-quality grid is one Technological difficulties.

In the prior art, mainly using following methods：

1. Incremental insertion incremental method (incremental insertion algorithm).The method main thought is first The scatterplot collection of a pile random alignment is surrounded with a sufficiently large triangle, then the new point of insertion is concentrated from successively, constantly more New current Delaunay Triangulation, until being all inserted into finishing a little.When input point set is more, such as medical science Image, so as to cause method time-consuming more long.

2. plane triangulation graph (plane-sweep algorithm)].The method is using the thought of flat scanning, head First all of point is arranged from left to right, initial convex hull is constituted with leftmost three points, when scan line reaches new point, place Manage the point, will the point be scanned some point be connected, renewal convex hull, the region triangulation that just will so scan. When scan line reaches the point of rightmost, the point is processed, this completes the triangulation of plane dotted line collection.

Therefore, it is necessary to be made improvements to the treatment of existing medical image networkization.

【The content of the invention】

The technical problems to be solved by the invention are to provide the gridding processing method and its system of a kind of medical image, use The multiple semi-cylindrical hills grid density degree in flexible modulation medical image, to improve mesh quality, meets follow-up visit need Ask.

In order to solve the above technical problems, the present invention discloses a kind of gridding processing method of medical image, methods described bag Include：

A two dimensional image is obtained, the two dimensional image includes one or more regions interested；

Extract multiple profile points of one or more of area-of-interests；

According to the multiple profile point, a first area and a second area are determined；

Based on a first mesh generation control condition, the grid of the first area is generated；

Based on a second mesh generation control condition, the grid of the second area is generated, wherein, second grid Divide control condition and be different from the first mesh generation control condition；And

The grid of grid and the second area according to the first area, to one or more of area-of-interests It is analyzed.

Further, one or more of area-of-interests include coronary artery, abdominal artery, arteriae cerebri, brain At least one of or artery of lower extremity.

Further, the grid of the grid of the first area or the second area is calculated based on Delaunay Triangulation Method is generated.

Further, the first mesh generation control condition includes a first area-constrained condition.

Further, the described first area-constrained condition includes that the area of all grids is not more than an area-constrained value.

Further, the second mesh generation control condition includes a second area constraints, wherein, described the Two area-constrained conditions are different from the described first area-constrained condition.

Further, methods described also includes determining the 3rd region according to the multiple profile point, wherein, described the Three regions do not carry out mesh generation.

Further, the analysis is carried out to the area-of-interest to be included analyzing institute according to Fluid Mechanics Computation (CFD) State a kinetic parameter of area-of-interest.

Further, methods described also includes：

A 3-D view is obtained, the 3-D view includes one or more of area-of-interests；And

The grid of grid and the second area according to the first area, generation corresponds to the one of the 3-D view Individual three-dimensional grid.

In order to solve the above technical problems, the present invention discloses a kind of gridding processing system of medical image, the system bag Include：

One receiver module, is configured as：

A two dimensional image is obtained, the two dimensional image includes one or more regions interested；And

One multidate feature generation module, is configured as：

Extract multiple profile points of one or more of area-of-interests；

In order to solve the above technical problems, the present invention discloses a kind of medical image network processing method, methods described includes：

Obtain the image and an image for the second phase of first phase；

First angiosomes is selected in the image of the first phase, wherein, first angiosomes is included One blood vessel；

Second angiosomes is selected in the image of second phase, wherein, second angiosomes is included The blood vessel at least partially；

First vascular pattern is set up, wherein, first vascular pattern is corresponding with first angiosomes；

Second vascular pattern is set up, wherein, second vascular pattern is corresponding with second angiosomes；

First vascular pattern and second vascular pattern are carried out at gridding according to the method for claim 1 Reason；

Set the boundary condition of first vascular pattern and the boundary condition of second vascular pattern；

According to the boundary condition of first vascular pattern, determine blood vessel described in first vascular pattern described The state of one phase；

Based on the blood vessel in the state of the first phase, first vascular pattern and the second blood vessel mould are associated Type, association first vascular pattern and second vascular pattern include the grid of matching first vascular pattern and The grid of second vascular pattern；And

According to the association results and the boundary condition of second vascular pattern, in determining second vascular pattern State of the blood vessel in second phase

Further, methods described includes：

Two-dimensional mesh is carried out to the entrance and exit of first vascular pattern to format treatment；

Side wall to first vascular pattern carries out gridding treatment；And

Gridding result based on the entrance, outlet and side wall, three dimensional network is carried out to first vascular pattern Format treatment.

Further, methods described includes：

Two-dimensional mesh is carried out to the entrance and exit of second vascular pattern to format treatment；

Side wall to second vascular pattern carries out gridding treatment；And

Gridding result based on the entrance, outlet and side wall, three dimensional network is carried out to second vascular pattern Format treatment.

In order to solve the above technical problems, asking that the present invention discloses a gridding processing system for medical image, the system Including：

At least one processor；And

Memory, for store instruction, when the instruction is by least one computing device, causes the system reality Existing operation includes：

Extract multiple profile points of one or more of area-of-interests；

Present invention contrast prior art has following beneficial effect：(1) net in human medical two-dimensional image plane is provided Lattice show that mess generation is time-consuming few；(2) not same district is flexibly controlled by the first mesh generation control condition and second condition The grid density degree in domain, the observation demand different to meet user；(3) present invention is applied to treatment two dimension, three-dimensional or four-dimensional Deng the gridding result of various dimensions；(4) grid and the grid of the second area according to the first area, to described One or more area-of-interests carry out including but not limiting visualization, image segmentation, the state analysis of tissue, Computational Mechanics The field such as analysis and medical diagnosis on disease, meets the different diagnosis and treatment demand of user.

【Brief description of the drawings】

Fig. 1 a and Fig. 1 b are the network environments including blood flow state analysis system shown in some embodiments of the invention；

Fig. 2 is a structure for computing device shown in some embodiments of the present invention, and the computing device can implement this The particular system disclosed in application；

Fig. 3 is a structural representation for mobile device shown in some embodiments of the present invention, and the mobile device can be with Implement the particular system disclosed in the application；

Fig. 4 a are the example modules schematic diagrames of the processing equipment shown in some embodiments of the present invention；

Fig. 4 b are the exemplary process diagrams of the multidate characteristic processing shown in some embodiments of the present invention；

Fig. 5 is the example modules schematic diagram of the multidate feature generation module shown in some embodiments of the present invention；

Fig. 6 is the exemplary process diagram of the gridding treatment of the medical image shown in some embodiments of the present invention；

Fig. 7 is the schematic diagram of the borderline region gridding treatment shown in some embodiments of the present invention；

Fig. 8 is the exemplary process diagram of the grid treatment of the medical image shown in some embodiments of the present invention.

【Specific embodiment】

Elaborate many details in order to fully understand the present invention in the following description.But the present invention can be with Much it is different from other manner described here to implement, those skilled in the art can be in the situation without prejudice to intension of the present invention Under do similar popularization, therefore the present invention is not limited by following public specific implementation.

Secondly, the present invention is described in detail using schematic diagram, when the embodiment of the present invention is described in detail, for purposes of illustration only, institute It is embodiment to state schematic diagram, and it should not limit the scope of protection of the invention herein.

In order to solve the above technical problems, the present embodiment is provided

In order to illustrate more clearly of the technical scheme of embodiments herein, below will be to make needed for embodiment description Accompanying drawing is briefly described.It should be evident that drawings in the following description are only some examples or the implementation of the application Example, for one of ordinary skill in the art, on the premise of not paying creative work, can also be according to these accompanying drawings The application is applied to other similar scenes.Unless obviously or separately explained from language environment, identical label generation in figure The identical structure of table or operation.

As shown in the application and claims, unless context clearly points out exceptional situation, " one ", " one ", " one The word such as kind " and/or " being somebody's turn to do " not refers in particular to odd number, may also comprise plural number.It is, in general, that term " including " only point out bag with "comprising" Include the step of clearly identifying and element, and these steps and element do not constitute one it is exclusive enumerate, method or equipment It is likely to comprising the step of other or element.

Although the application is made that various drawing to some of the data handling system according to embodiments herein module With, however, any amount of disparate modules can by using and operate in a client being connected with the system by network And/or on server.The module is merely illustrative, and the different aspect of the system and method can use different moulds Block.

Flow chart used herein is used for illustrating according to performed by the data handling system of embodiments herein Operating procedure.It should be appreciated that be displayed in the operating procedure of above or below not necessarily accurately carrying out in sequence.Phase Instead, various steps can be processed according to inverted order or simultaneously.It is also possible to other operating procedures are added to during these, Or remove a certain step or number step operation from these processes.

During image real time transfer, " image segmentation ", " image zooming-out ", " image classification " can be converted mutually, Express the image chosen from extensive area and meet certain condition.In certain embodiments, imaging system can include it is a kind of or Variform.The form is included but is not limited to, digital subtraction angiography (DSA), magnetic resonance imaging (MRI), magnetic resonance blood Pipe radiography (MRA), computed tomography (CT), computed tomography angiography (CTA), ultrasonic scanning (US), just Positron emission tomography art (PET), single photon emission computerized tomography,SPECT (SPECT), SPECT-MR, CT-PET, CE- SPECT, DSA-MR, PET-MR, PET-US, SPECT-US, TMS-MR, US-CT, US-MR, X-ray-CT, X-ray-PET, X are penetrated Line-US, video-CT, video-US and/or similar one or more of combination.In certain embodiments, the mesh of image scanning Mark can be the combination of one or more of organ, body, object, damage location, tumour etc..In certain embodiments, imaging is swept The target retouched can be the combination of one or more of head, thoracic cavity, belly, organ, bone, blood vessel etc..In certain embodiments, The target of scanning can be the vascular tissue at one or more positions.In certain embodiments, image can be two dimensional image and/ Or 3-D view.In two dimensional image, most trickle resolvable elements can be pixel (pixel).In 3-D view, most Trickle resolvable elements can be tissue points (voxel).In 3-D view, image can be by a series of two dimension slicing or two Dimension figure layer is constituted.

The individual features of the pixel (or tissue points) that image segmentation process can be based on image are carried out.In some embodiments In, the individual features of the pixel (or tissue points) can include texture structure, gray scale, average gray, signal intensity, color The combination that one or more of saturation degree, contrast, brightness etc..In certain embodiments, the sky of the pixel (or tissue points) Between position feature can be used for image segmentation process.

The application is related to the gridding processing method of a medical image and system, can apply to image viewing, figure As segmentation, the state analysis of tissue, the field such as Computational Mechanics analysis and medical diagnosis on disease.

Hereinafter the present invention is described in detail only by taking blood flow state analysis method and its system as an example.Blood flow state analysis system The 100 multiple vascular patterns of association, during blood flow state analysis system is obtained, obtain the image of multiple phases, set up with it is many Individual phase distinguishes corresponding multiple vascular patterns.Set the boundary condition of the multiple vascular pattern respectively according to association results, Determine the blood vessel state of the multiple vascular pattern.

Fig. 1 a are including blood flow state analysis system 100 according to some embodiments of the present application.The blood flow state Analysis system 100 can include data acquisition equipment 110, processing equipment 120, storage device 130 and display device 140.Data Collecting device 110, processing equipment 120, storage device 130 and interactive device 140 can be led to by network 180 each other Letter.

Data acquisition equipment 110 can be an equipment for gathered data.The data can include view data, object Characteristic etc..In certain embodiments, the data acquisition equipment 110 can include an imaging device.The imaging sets It is standby to gather described image data.The imaging device can be magnetic resonance imager (magnetic resonance Imaging, MRI), computed tomographic scanner (computed tomography, CT), positron emission computer Layer displaing image instrument (positron emission computed tomography, PET), B ultrasonic instrument (b-scan Ultrasonography), diasonograph (diasonography) hot OCT (Thermal texture maps, TTM), the combination of one or more in medical electronic endoscope (medical electronic endoscope, MEE) etc.. Described image data can be the picture or data for including the blood vessel, tissue or organ of object.In certain embodiments, the number Can include a characteristics of objects collecting device according to collecting device.The characteristics of objects collecting device can be with the heart of acquisition target Rate, the rhythm of the heart, blood pressure, blood flow rate, blood viscosity, cardiac output, myocardial mass, blood vessel flow resistance, and/or other and blood Pipe, tissue or the related characteristics of objects data of organ.In certain embodiments, the characteristics of objects collecting device can obtain right As other characteristics of objects data such as age, height, body weight, sex.In certain embodiments, described image data and characteristics of objects Data can be multi-temporal data.For example, the multi-temporal data can be the object obtained in different time points or phase Identical or apparent position data with it.In certain embodiments, the characteristics of objects collecting device can be integrated in it is described into As in equipment, so as to gather view data and characteristics of objects data simultaneously.In certain embodiments, the data acquisition equipment 110 data is activations that can be gathered it by network 180 are to processing equipment 120, storage device 130 and/or interactive device 140。

Processing equipment 120 can be processed data.The data can be collected by data acquisition equipment 110 Data, from storage device 130 read data, the input number of the feedback data obtained from interactive device 140, such as user According to, or the data obtained from high in the clouds or external equipment by network 180 etc..In certain embodiments, the data can be with Including view data, characteristics of objects data, user input data etc..The treatment selects sense emerging in being included in view data The region of interest.The region interested can voluntarily be selected by processing equipment 120 or be selected according to user input data.One In a little embodiments, the area-of-interest of selection can be blood vessel, tissue or organ etc..For example, the area-of-interest can be with It is arteries, such as coronary artery, abdominal artery, arteriae cerebri, artery of lower extremity.Processing equipment 120 can further to institute State and region interested is split in image.The method of image segmentation can include the image partition method based on edge, Such as Perwitt Operator Methods, Sobel Operator Methods, gradient operator method, Kirch Operator Methods, the image partition method based on region, Such as region-growing method, threshold method, clustering procedure and other dividing methods, are such as based on fuzzy set, the method for neutral net.

Processing equipment 120 can carry out Model Reconstruction to the area-of-interest.The selection of model can be special based on object Levy data, feature of area-of-interest etc..If for example, have selected region interested for coronary artery, processing equipment 120 can With to being split so as to extract image coronarius comprising image coronarius.Then, processing equipment 120 can be with root The reconstruction of model is carried out according to characteristics of objects, coronary artery general features, coronary artery images feature etc..The model of reconstruction can be with The shape of coronary artery is corresponding, it is also possible to which the form with blood flow in coronary artery is corresponding.It is interested setting up After the model in region, processing equipment 120 can be analyzed and calculate according to model.The analysis and the method for calculating can be wrapped Include Fluid Mechanics Computation (Computed fluid dynamics) etc..

In certain embodiments, processing equipment 120 can obtain the data of multidate, and such as object is in 5 different time points The image of upper coronary artery region.In this case, processing equipment 120 can to the area-of-interest of different phases (for example, Whole coronary artery, the branch on coronary artery, or blood entry port section coronarius etc.) image build mould respectively Type, then model is analyzed and calculated successively.In certain embodiments, processing equipment 120 can be to the different phases Model carries out gridding treatment, and model after processing gridding carry out it is interrelated, so as to reduce amount of calculation, improve and calculate The degree of accuracy.It is mutually related on gridding treatment and model and illustrates to may refer to the application description elsewhere, for example, figure 7 and its description.In certain embodiments, the analysis and the result for calculating can include the physics shape of blood vessel, tissue or organ State and coefficient correlation or parameter.For example, arteria coronaria model is analyzed and the result that calculates can include it is coronarius Hemodynamic parameter, such as blood flow rate, blood pressure, blood vessel wall stress, Wall shear stress, blood flow reserve coefficient or blood flow Deposit fraction (Fractional Flow Reserve, FFR), CFR (Coronary Flow Reserve, ) etc. CFR one or more in of combination.In certain embodiments, processing equipment 120 can according to the analysis of different phases and Result of calculation generates the physical state and/or coefficient correlation or parameter with phase or the relation of time (for example, Hemodynamics Parameter changes with time).The relation can be embodied with the mode of curve or the table of comparisons.Based on the curve or the table of comparisons, Processing equipment 120 can obtain the physical state and/or coefficient correlation or parameter of the area-of-interest of any phase.

In certain embodiments, the data or result that processing equipment 120 can be obtained to it carry out noise reduction or smooth Treatment.In certain embodiments, the data or result that processing equipment 120 can be obtained are sent to storage device 130 Stored, or transmission to interactive device 140 is shown.The result can be the centre of generation in processing procedure As a result, such as the model, or the final result for the treatment of of area-of-interest, the haemodynamics ginseng such as analyzed and calculate Number etc..In certain embodiments, processing equipment 120 can be one or more treatment elements or equipment, such as central processing unit (central processing unit, CPU), graphic process unit (graphics processing unit, GPU), numeral letter Number processor (digital signal processor, DSP), System on Chip/SoC (system on a chip, SoC), microcontroller Device (microcontroller unit, MCU) etc..In certain embodiments, processing equipment 120 can also be the tool of particular design The treatment element or equipment of standby specific function.Processing equipment 120 can be local, or be relative to data acquisition equipment 110 Long-range.

Storage device 130 can store data or information.The data or information can be obtained including data acquisition equipment 110 The user received by data, the result of the generation of processing equipment 120 or control instruction and interactive device 140 for taking is defeated Enter data etc..Storage device 130 can be one or more storage medium that can be read or write, including but not limited to static Random access memory (static random access memory, SRAM), random access memory (random-access memory, RAM), read-only storage (read-only memory, ROM), hard disk, flash memory etc..In certain embodiments, storage device 130 Can also be long-range memory, such as cloud disk.

Interactive device 140 can be received, sent, and/or display data or information.The data or information of the reception can With obtained including data acquisition equipment 110 data, processing equipment 120 produce result, storage device 130 store number According to etc..For example, the data or information of the display of interactive device 140 can include cardiovascular reality that data acquisition equipment 110 is obtained The cardiovascular model 160 that border image 150, processing equipment 120 are set up according to real image 150, and processing equipment 120 is from the heart Arteria coronaria model 170 extracted in vascular pattern 160 etc..The form of display can include but is not limited to two-dimentional or three-dimensional Medical image, geometrical model and its network analysis, polar plot (such as velocity line), isogram, the isogram of filled-type One or more combination such as (cloud atlas), XY scatter diagrams, particle trajectory figure, simulation flow effect.Again for example, interactive device 140 is sent out The data or information sent can include the input information of user.Interactive device 140 can receive the processing equipment 120 of user input One or more operational factors, and be sent to processing equipment 120.

In certain embodiments, interactive device 140 can include a User Interface.User can be by specific Interactive device, such as mouse, keyboard, touch pad, microphone are input into a user input data to interactive device 140.For example, with Family can click on region interested in model shown by interactive device 140 and preference pattern.Again for example, user can select Arbitrary position in vascular pattern shown by interactive device 140, interactive device 140 can be obtained and shown from processing equipment 120 Show Hemodynamic environment, blood pressure, CBF of the position etc..

In certain embodiments, interactive device 140 can be the equipment with display function such as display screen.In some implementations In example, interactive device 140 can have all or part of function of processing equipment 120.For example, interactive device 140 can be to place The operations such as the result of the generation of reason equipment 120 is smoothed, noise reduction, discoloration.For example, color change operation can be by a gray-scale map Become coloured picture, or a coloured picture is become into a gray-scale map.In certain embodiments, interactive device 140 can with processing equipment 120 Being an integrated equipment.The integrated equipment can simultaneously realize the function of processing equipment 120 and interactive device 140. In certain embodiments, interactive device 140 can be including desktop computer, server, mobile device etc..Mobile device can include Notebook computer, panel computer, ipad, built-in device, the wearable device of the vehicles (for example, motor vehicle, ship, aircraft etc.) Deng.In certain embodiments, interactive device 140 can include or be connected to display device, printer, fax etc..

The communication that network 180 can be used for inside blood flow state analysis system 100, the information outside reception system, to being Outside transmission information of system etc..In certain embodiments, between data acquisition equipment 110, processing equipment 120 and interactive device 140 Can be wired connection, wireless connection or access network 180 by way of its combination.Network 180 can be single network, It can be the combination of multiple network.In certain embodiments, network 180 can include but is not limited to LAN, wide area network, public One or more in network, dedicated network, WLAN, virtual network, city Metropolitan Area Network (MAN), public switch telephone network etc. Combination.In certain embodiments, network 180 can include multiple network access point, such as wired or wireless access point, base station Or network exchange point, data source is connected network 180 and information is sent by network by above access point.

Shown in Fig. 1 b is another schematic diagram of blood flow state analysis system 100.Fig. 1 b are similar with Fig. 1 a.Fig. 1 b In, processing equipment 120 can be joined directly together with data acquisition equipment 110, and data acquisition equipment 110 is not direct with network 180 It is connected.

Description above is only specific embodiment of the invention, is not considered as unique embodiment.Clearly for For one of skill in the art, after understand present invention and principle, all may be without departing substantially from the principle of the invention, structure In the case of, carry out various amendments and the change in form and details.For example, data acquisition equipment 110, processing equipment 120, interaction The exchange of data or information can not be directly carried out between equipment 140 by network 180.Again for example, these equipment can also The exchange of data or information is carried out by way of removable memory or other intermediarys.

Fig. 2 is a structure for computing device 200 according to some embodiments of the present application.The computing device 200 The particular system disclosed in the application can be implemented.Particular system in the present embodiment explains one and includes using functional block diagram The hardware platform of user interface.Computing device 200 can implement currently to describe one or many in blood flow state analysis system 100 Individual component, module, unit, subelement (for example, processing equipment 120, interactive device 140 etc.).In addition, blood flow state analysis system One or more assemblies, module, unit, subelement (for example, processing equipment 120, interactive device 140 etc.) in 100 can be by Computing device 200 is realized by its hardware device, software program, firmware and combinations thereof.This computer can be The computer of one general purpose, or one have the computer of specific purpose.Two kinds of computers can be used for reality Particular system in existing the present embodiment.For convenience's sake, a computing device is only depicted in Fig. 2, but the present embodiment institute The correlation computer function of carrying out information processing and pushed information of description can be in a distributed fashion, it is similar flat by one group What platform was implemented, the treatment load of decentralized system.

As shown in Fig. 2 computing device 200 can include internal communication bus 210, processor (processor) 220, only Reading memory (ROM) 230, random access memory (RAM) 240, COM1 250, input output assembly 260, hard disk 270, User interface 280.Internal communication bus 210 can realize the data communication of the inter-module of computing device 200.Processor 220 can be with Execute program instructions complete to disclose herein the one or more functions of blood flow state analysis system 100 described in book, component, Module, unit, subelement.Processor 220 is made up of one or more processors.COM1 250 can configure realization and calculate Data communication (is such as led between equipment 200 and the miscellaneous part of blood flow state analysis system 100 (such as data acquisition equipment 110) Cross network 180).Computing device 200 can also include the program storage unit and data storage element of multi-form, for example firmly Disk 270, read-only storage (ROM) 230, random access memory (RAM) 240, can be used in computer disposal and/or communication makes Various data files, and the possible programmed instruction performed by processor 220.Input output assembly 260 is supported to calculate Equipment 200 and other assemblies (such as user interface 280), and/or with the other assemblies of blood flow state analysis system 100 (such as database 140) input/output data stream between.Computing device 200 can also be sent and received by COM1 250 from network 180 Information and data.

Fig. 3 describes a kind of structure of mobile device, and the mobile device is implemented for implementing in the application what is disclosed Particular system.In this example, for showing that the user equipment with interaction locations relevant information is a mobile device 300.It is mobile Equipment 300 can include that smart mobile phone, panel computer, music player, portable game, global positioning system (GPS) are received Device, wearable computing devices (such as glasses, wrist-watch), or other forms.Mobile device 300 in this example includes one or many Individual central processing unit (CPUs) 340, one or more graphic process unit (graphical processing units (GPUs)) 330, a display 320, an internal memory 360, an antenna 310, such as one wireless communication unit, memory cell 390, and One or more input/output (input output (I/O)) equipment 350.Any other suitable component, including but not limited to System bus or controller (not shown on figure), it is also possible to be included in mobile device 300.As shown in figure 3, a mobile behaviour Make system 370, such as iOS, Android, Windows Phone, and one or more can be from memory cell using 380 390 load into internal memory 360, and performed by central processing unit 340.A browser is potentially included using 380 or other are suitable Close the Mobile solution that image or blood status analysis relevant information are received and processed on mobile device 300.User and blood flow shape Interaction of the one or more assemblies on image or blood status analysis relevant information can be by defeated in state analysis system 100 Enter/output system equipment 350 be obtained and provided in processing equipment 120, and/or blood flow state analysis system 100 other Component, for example：By network 180.

According to some embodiments of the present application, Fig. 4 is the example modules schematic diagram of processing equipment.Processing equipment 120 can With including receiver module 410, control module 420, multidate feature generation module 430, multidate feature processing block 440 and defeated Go out module 450.

Receiver module 410 can obtain view data, characteristics of objects from data acquisition equipment 110 and/or storage device 130 Data etc..Described image data can be the picture or data for including the blood vessel, tissue or organ of object.The characteristics of objects number According to heart rate, the rhythm of the heart, blood pressure, blood flow rate, blood viscosity, cardiac output, myocardial mass, the blood vessel flow resistance that can include object And other to blood vessel, tissue or the related characteristics of objects data of organ and subject age, height, body weight, sex etc. other Characteristics of objects data.In certain embodiments, described image data and characteristics of objects data can be multi-temporal datas.For example, The multi-temporal data can be identical or apparent position data with the object obtained in different time points or phase.

Control module 420 can send control instruction.Control instruction can control other modules to be input into, exported, deposited The operations such as storage, treatment.For example, the control instruction can receive required data with control receiver module 410.Again for example, institute Stating control instruction can control multidate feature generation module 430 to generate feature of multidate etc..

Multidate feature generation module 430 can generate multidate feature.The multidate feature can include multidate Model, multidate parameter, multidate boundary condition, analysis result of multidate etc..More specifically, multidate feature generation module 430 can respectively select region interested in multi-temporal image data.The region interested can be special by multidate Generation module 430 is levied voluntarily to select or selected according to user input data.In certain embodiments, the area-of-interest of selection can Being blood vessel, tissue or organ etc..For example, the area-of-interest can be arteries, such as coronary artery, belly are moved Arteries and veins, arteriae cerebri, artery of lower extremity etc..The area-of-interest selected in the multi-temporal image can be corresponding.For example, can With comprising at least part of identical blood vessel, tissue or organ etc..Multidate feature generation module 430 can further to described Split in region interested in multi-temporal image.The method of image segmentation can include the image segmentation side based on edge Method (such as Perwitt Operator Methods, Sobel Operator Methods, gradient operator method, Kirch Operator Methods), the image segmentation side based on region Method (such as region-growing method, threshold method, clustering procedure), and other dividing methods, are such as based on fuzzy set, the method for neutral net Deng.In certain embodiments, multidate feature generation module 430 can be carried out to region interested in multi-temporal image simultaneously Segmentation.In certain embodiments, multidate feature generation module 430 can enter to region interested in multi-temporal image successively Row segmentation.

Multidate feature generation module 430 can carry out Model Reconstruction to the area-of-interest, so as to generate multidate Model.The selection of model can be based on characteristics of objects data, feature of area-of-interest etc..If for example, have selected interested Region be coronary artery, multidate feature generation module 430 can be to being split so as to carry comprising image coronarius Take out image coronarius.Then, multidate feature generation module 430 can be typically special according to characteristics of objects, coronary artery Levy, coronary artery images feature etc. carries out the reconstruction of model.The model of reconstruction can be corresponding with the shape of coronary artery, Or it is corresponding with the form of blood flow in coronary artery.After the model for setting up area-of-interest, multidate feature generation mould Block 430 can be analyzed and calculate with arrange parameter and boundary condition and according to model.Specific parameter and boundary condition are set Method and analysis method may refer to the description of the application other parts.

Multidate feature processing block 440 can be processed the multidate result of calculation of generation (to be located after also referred to as Reason).The treatment can be using the result of calculation of the method generation model such as fitting, interpolation and the relation curve or right of phase According to table.According to the relation curve or the table of comparisons, multidate feature processing block 440 can further generate dividing for any phase Analyse the estimate of result.In certain embodiments, the multidate that the multidate feature processing block 440 will can be generated is calculated As a result (for example, blood vessel state) and a reference result are compared and generate one and compare conclusion.The reference result can be with The data in storage device 130 are stored in, the data, or user that can be stored in network 180 are voluntarily input into Data.In certain embodiments, the reference result and correlation ratio can be stored in a table to conclusion.For example, described When result of calculation is blood flow rate, the reference result can be the corresponding relation of a blood flow rate scope and degree of danger. The degree of danger can be divided into normally, early warning, danger, be in extreme danger.In certain embodiments, user can be according to clinic Experience is manually entered the corresponding relation.In certain embodiments, the comparison can be the blood flow of same target different times The comparison of the result of calculation of speed.

Output module 450 can be exported the multidate result of calculation or data of generation.For example, output module 450 Multidate result of calculation or feature can be sent to storage device 130 and be stored, or transmission to interactive device 140 is carried out Display.In certain embodiments, multidate feature processing block 440 or output module 450 can before output to it is described many when Phase character or result of calculation carry out noise reduction or smoothing processing.The multidate result of calculation can be the intermediate result of generation, such as The model of area-of-interest, or the final result for generating, the hemodynamic parameter such as analyzed and calculate or result of calculation With the relation curve or the table of comparisons of phase etc..

According to some embodiments of the present application, Fig. 4 b are the exemplary process diagrams of multidate characteristic processing.In some implementations In example, flow 400 can be realized by processing equipment 120.

In 462, one or more control instructions can be produced.In certain embodiments, 462 can be by control module 420 realize.The control instruction can be with the carrying out of other steps in control flow 400.

In 464, multi-temporal data can be received.In certain embodiments, 464 can be realized by receiver module 410. The multi-temporal data can include multi-temporal image data and multidate characteristics of objects data.In certain embodiments, it is described Multidate characteristics of objects data can be characteristics of objects data or indicatrix continuous in time.

In 466, multidate feature can be generated.In certain embodiments, 466 mould can be generated by multidate feature Block 430 is realized.The multidate feature can include multidate model, multidate parameter, multidate boundary condition, multidate Analysis result etc..

In 468, the multidate feature for generating can be processed.In certain embodiments, 468 can by it is many when Phase character processing module 440 is realized.The treatment can generate multidate feature and phase using methods such as fitting, interpolation Relation curve or the table of comparisons.

In 470, multidate feature or result can be exported.In certain embodiments, 470 can be by exporting mould Block 450 is realized.In certain embodiments, 468 can be skipped, the multidate feature output that will directly generate.

According to some embodiments of the present application, Fig. 5 is the example modules schematic diagram of multidate feature generation module.When many Phase character generation module 430 can include data capture unit 510, parameter set unit 520, computing unit 530, mess generation Unit 540, matching unit 550, area selecting unit 560, output unit 570 and judging unit 580.

Data capture unit 510 can from multidate feature generation module 430 other units, blood flow state analysis system In 100 data are obtained in other equipment or module or external device or module.The data can include that view data, object are special Levy data, user input data etc..Described image data can be the picture or number for including the blood vessel, tissue or organ of object According to.The characteristics of objects data can include the heart rate of object, the rhythm of the heart, blood pressure, blood flow rate, blood viscosity, cardiac output, Myocardial mass, blood vessel flow resistance and other to blood vessel, tissue or the related data of organ.In certain embodiments, described image Data and characteristics of objects data can be multi-temporal datas.In certain embodiments, data capture unit 510 can set from storage Data after treatment, the vascular pattern such as rebuild are obtained in standby 130.In certain embodiments, data capture unit 510 can pre-process to the view data for obtaining.The pretreatment can include that image enhaucament, image noise reduction, image are put down It is sliding etc..

Parameter set unit 520 can be with preference pattern and arrange parameter and boundary condition.The selection of the model can be with It is suitable including diseased region (area-of-interest) and characteristics of objects data (such as blood viscosity) selection according to concrete analysis The blood Viscosity Model and flow velocity boundary model of conjunction.The blood Viscosity Model can include Newtonian fluid model, non-newtonian flow Body Model and user-defined other fluid models.The Newtonian fluid model can be used to blood in simulated object body and glue The more constant region of denseness, and non-Newtonian models can be used to the non-constant area of blood viscosity in simulated object body Domain.The flow velocity boundary model can include parabola model, hyperbolic model, model of ellipse, average flow model, Womersley distributed models, Reynolds models, mixed model etc..In certain embodiments, the setting of the parameter can be wrapped Include the setting of selected Model Parameter, such as the blood viscosity in Newtonian fluid model, the blood in Newtonian fluid model Liquid-tight degree, the time step number in simulation calculating, the time step in simulation calculating etc..

Computing unit 530 can enter to the data or information that are produced in other units in multidate feature generation module 430 Row is calculated.In certain embodiments, computing unit 530 can generate a corresponding model according to view data.Institute The generation for stating model can be based on the selected types of models of parameter set unit 520 and the parameter for setting.In some embodiments In, computing unit 530 can be analyzed and calculate after the model for setting up area-of-interest to model.The analysis and meter The method of calculation can include Fluid Mechanics Computation (Computed fluid dynamics) etc..In certain embodiments, described point Analysis and the result for calculating can include the physical state and coefficient correlation or parameter of blood vessel, tissue or organ.For example, to coronal Artery model is analyzed and the result that calculates can include hemodynamic parameter coronarius, such as blood flow rate, blood In pressure, blood vessel wall stress, Wall shear stress, blood flow reserve coefficient (FFR), CFR (CFR) etc. one Plant or various combinations.

In certain embodiments, the information and data that computing unit 530 is calculated can be multidates.Computing unit 530 can be analyzed and calculate to the information and data of the multidate respectively.In certain embodiments, computing unit 530 Can according to the physical state and/or coefficient correlation or parameter of the analysis of different phases and result of calculation generation area-of-interest with Phase or the relation of time.In certain embodiments, the relation can be embodied with the mode of curve or the table of comparisons.Based on described Curve or the table of comparisons, can obtain the physical state and/or coefficient correlation or parameter of the area-of-interest of any phase.At some In embodiment, the physical state and relevant parameter coefficient of the area-of-interest of the curve, the table of comparisons or any phase can be with It is sent to outside other modules of blood flow state analysis system 100 or unit or blood flow state analysis system 100 by output unit 570 In the module or unit on boundary.

Mess generation unit 540 can be in the grid of generation model.In certain embodiments, mess generation unit 540 can To generate the grid of two dimension or three-dimensional on model.For example, mess generation unit 540 can model borderline region (entrance, Outlet etc.) the two-dimentional grid of generation, and in the three-dimensional grid of other Area generations of model.The three-dimensional grid can be based on The two-dimensional grid and set up.Specific method and flow on grid protocol may refer to, and such as Fig. 6, Fig. 8 and its retouch State.

Matching unit 550 can be matched to the data of multidate.In certain embodiments, matching unit 550 can be with The model of different phases is carried out interrelated.The model of the different phases can be by the model after gridding treatment. In certain embodiments, the model process of being mutually related of the different phases can include first identifying the model of different phases In characteristic area.Then, the corresponding characteristic area of different phases is associated.If for example, the different phases Model is flow model (model of blood flow overlay area in blood vessel i.e. interested), and the characteristic area can be flowed into including blood Mouth region domain, blood flow bifurcation region, blood stream outlet region, blood flow narrow zone, bloodstream invasion region etc..Then, matching unit 550 The individual features region of different phases can be associated.In certain embodiments, a characteristic area can in different phases The grid of the different numbers of energy correspondence.In this case, grid of the characteristic area in different phases can rely on certain Algorithm or method are associated.For example, multiple grids correspond to a grid or a small number of nets in the second phase in working as first phase During lattice, matching unit 550 numerical value of multiple grid in first phase can be averaged after treatment again with described second when The numerical value of one or a small number of grid carries out correspondence in phase.In certain embodiments, in the calculating of initial phase, can be by inside The initial value (for example, pressure initial value, speed initial value etc.) of grid (the not grid including borderline region in grid model) sets It is set to 0.In the calculating of follow-up phase, it is possible to use mesh fitting by the inner mesh result of calculation of a upper phase map or It is assigned in the corresponding grid of the inner mesh of current phase, and as the initial value of current phase grid.In some embodiments In, matching unit 550 can point out user to confirm whether matching is accurate after matching is completed.If user confirms that matching is accurate Carry out follow-up process.If the user thinks that matching is inaccurate, then user can be modified or adjust to matching result.User Can select to re-start mesh fitting in the case of its participation.

Area selecting unit 560 can select region interested in view data.The region interested can be with Voluntarily selected by area selecting unit 560 or selected according to the information of user input.In certain embodiments, selection is interested Region can be blood vessel, tissue or organ etc..Area selecting unit 560 can further in described image to interested Split in region.The method of image segmentation can include based on edge image partition method, such as Perwitt Operator Methods, Sobel Operator Methods, gradient operator method, Kirch Operator Methods etc., the image partition method based on region, such as region-growing method, threshold value Method, clustering procedure etc. and other dividing methods, are such as based on fuzzy set, the method for neutral net.Area selecting unit 560 can be with Enter full-automatic dividing or semi-automatic segmentation.If for example, selection area-of-interest be coronary artery, abdominal artery, brain move Arteries and veins, artery of lower extremity etc., area selecting unit 560 can be split automatically.If the area-of-interest of selection is other machines The blood vessel of more difficult accurate segmentation or position, then can carry out semi-automatic segmentation, be modified in cutting procedure by user.One In a little embodiments, area selecting unit 560 can carry out regional choice and segmentation to the threedimensional model rebuild according to view data.

Output unit 570 can be by information, the number produced by one or more units in multidate feature generation module 430 According to or during result sends other modules or unit into blood flow state analysis system 100.For example, output unit 570 can Shown so that the model that computing unit 530 is generated is sent to interactive device 140.Again for example, output unit 570 can be by The model that mess generation unit 540 is carried out after gridding treatment sends into storage device 130 and is stored.

Judging unit 580 can carry out logic judgment.For example, other modules or unit in blood flow state analysis system 100 One can be sent and judge request to judging unit 580.Judging unit 580 can judge that request is entered to corresponding contents according to described Row judges.After particular case or generation judged result is judged, judging unit 580 can will determine that result or corresponding operation Instruction is sent to corresponding module or unit (for example, sending the module or unit for judging request).For example, judging unit 580 can To judge the blood vessel to be analyzed of area selecting unit 560 with the presence or absence of abnormal (such as hemadostewnosis, aneurysm etc.).If it is determined that Go out the blood vessel and there is exception, judging unit 560 can highlight (such as represented with different colors) abnormal vascular, and simultaneously Prompting user confirms whether the abnormal vascular meets the requirement of user.If it is satisfied, then carrying out subsequent operation；If be unsatisfactory for, Then user can manually select abnormal vascular, then carry out subsequent operation.For example, area selecting unit 560 can select user The region of the area-of-interest selected and its own generation is sent to judging unit 580, and judging unit 580 may determine that the sense is emerging Whether the region of interesting region and the generation of area selecting unit 560 is identical.If it is determined that unit 580 judges user and regional choice The region of the generation of unit 560 is identical, then can send instructions to area selecting unit 560 makes it carry out further segmentation portion Reason.Otherwise, the selection of user can be reaffirmed by display device 140.

Description above is only specific embodiment of the invention, is not considered as unique embodiment.Clearly for For one of skill in the art, after understand present invention and principle, all may be without departing substantially from the principle of the invention, structure In the case of, carry out various amendments and the change in form and details.For example, above-mentioned each unit is said by taking Mono temporal as an example It is bright, but it is understood that the data that each unit is received, processes or exported can be multidate.For the number of multidate According to above-mentioned each unit can respectively carry out corresponding operating so as to produce the feature of multidate to the data of different phases.For example, net Lattice generation unit 530 can respectively carry out corresponding gridding treatment to the model of multidate, so as to generate the grid of multidate Model after change treatment.Again for example, parameter set unit 520 model of multidate or data can be respectively provided with it is corresponding Parameter or boundary condition.

According to some embodiments of the present application, Fig. 6 is the exemplary process diagram of gridding treatment；In certain embodiments, Flow 600 can be realized by mess generation unit 540.

In 602, a model can be obtained.The model can be the model of explanation in the application other embodiment, For example, the model after object blood vessel or blood flow, tissue or organ or the reconstruction of other area-of-interests.As shown in fig. 7,710 can be with It is region that a coronary blood flow model, i.e. model 710 can represent that blood flow is covered in coronary artery blood vessel.Do not considering vascular wall When thickness and blood vessel blockage, model 710 can also one coronary artery vascular pattern of approximate representation.

In 604, it may be determined that the borderline region of the model.If model is a blood vessel or blood corresponding with blood vessel Stream region, borderline region can be outlet, entrance, vascular wall of blood vessel etc..As shown in fig. 7, the entrance 720 of model 710 can be with It is confirmed as the borderline region of model 710 in 604.

In 606, can pair determine borderline region carry out surface grids division (also referred to as two-dimensional grid division).It is described It can be that the corresponding plane of borderline region is divided with grid that surface grids are divided.The partitioning algorithm of grid includes triangle gridding Divide, corner mesh generation, hexagonal gridding is divided, or similar, or the combination of one or more.Exemplary grid is drawn Dividing algorithm includes Loop algorithms, butterfly-type algorithm of subdivision, Catmull-Clark algorithms, Doo-Sabin algorithms, Delaunay triangles Partitioning algorithm etc..The method example of mesh generation may refer to Fig. 8 and its description.As shown in fig. 7,730 is the entrance of model 710 Sectional view, and 740 be 730 mesh generations example results.

In 608, surface grids division can be carried out to model side wall.In certain embodiments, side wall and borderline region can Divided with using different Meshing Methods.For example, side wall can carry out grid using surface mesh subdivision algorithm drawing Point.The algorithm of the surface mesh subdivision can be including reflection method and automatic mesh generation method etc..The reflection method can include Side wall is mapped into plane, after being divided to plane using two-dimensional grid division methods, then the mesh mapping after division is returned Side wall.Side wall can be divided into several almost planes again by the automatic mesh generation method according to the curvature of different zones in the wall of side Two-dimensional grid division is carried out respectively.Planar mesh is referred to the description in the application elsewhere, for example, Fig. 8 and Description.

In 610, can according to the surface grids division result of borderline region and side wall model is carried out volume mesh division ( It is referred to as three-dimensional grid division).It can be that model is divided with three-dimensional grid that the volume mesh is divided.The three dimensional network Lattice can include tetrahedral grid, hexahedral mesh, prism volume mesh (body fitted anisotropic mesh), tetrahedron and hexahedron hybrid network Lattice, cartesian grid, ball completion method grid etc..In certain embodiments, 604 to 608 can be skipped, you can with directly to mould Type carries out volume mesh division.

According to some embodiments of the present application, Fig. 8 is the exemplary process diagram of mesh generation.In certain embodiments, flow Journey 800 can be realized by multidate feature generation module 430.In certain embodiments, 606 in Fig. 6 etc. can be according to stream Journey 800 is implemented.

In 802, a two dimensional image can be obtained.In certain embodiments, the two dimensional image can be by data Acquiring unit 510 is obtained.In certain embodiments, two dimensional image can be a two-dimensional medical images, or wherein user's sense The part (for example, the region where coronary artery blood vessel, brain region etc.) of interest.Merely exemplary, two dimensional image can be one Individual CT images, MRI image, PET image etc..Two dimensional image can be showed in the way of gray scale or colour.In some realities Apply in example, two dimensional image can be a two dimension display for phase model.For example, two dimensional image can be in one and 606 The relevant image of the borderline region of phase model.More specifically, two dimensional image can show an inlet/outlet for flow model Region.Two dimensional image can be an image rebuild by image processing equipment (for example, processing equipment 120).Two dimensional image can With the storage device (for example, storage device 130) from a local storage or the external world.

In 804, mess generation unit 540 can extract the profile point of area-of-interest in two dimensional image.In some realities Apply in example, extracting the profile point of area-of-interest in two dimensional image includes first splitting area-of-interest, then emerging to the sense after segmentation Interesting extracted region profile point.The dividing method to area-of-interest is shown in the description in the application elsewhere.In some realities Apply in example, the profile point of area-of-interest can include that one or more are located at the pixel of region of interest border (also referred to as " wire-frame image vegetarian refreshments ").For example, the profile point at coronary artery entrance section can include that one or more are located at the wire-frame image of coronary artery wall Vegetarian refreshments.In certain embodiments, the wire-frame image vegetarian refreshments of area-of-interest can be continuous, and part is continuous, or discontinuously 's.It is mentioned here it is continuous refer to an adjacent wire-frame image vegetarian refreshments and at least one or more other wire-frame image vegetarian refreshments.Extract The information of profile point can be stored in one or more storage device (for example, storage device 130, memory module 260 Deng).The information of profile point can in follow-up process by mess generation unit 540 or other can carry out the list of data analysis Unit/module is used.The information of exemplary profile point can include the position of profile point, the quantity of profile point, or similar, Or the combination of one or more.

In 806, one or more regions can be determined according to profile point.In certain embodiments, it is one or many The determination in individual region can be realized by mess generation unit 540.One or more of regions can be by being sequentially connected sense The profile point in interest region is formed.It is merely exemplary, determine that one or more regions can include determining that a region of interest The initial profile pixel (for example, initial profile pixel can elect the point of x/y coordinates minimum in wire-frame image vegetarian refreshments as) in domain.Press According to direction pivots clockwise or counter-clockwise, the contour pixel point of area-of-interest is ranked up.Since initial profile pixel, With the previous wire-frame image vegetarian refreshments of line and curve connection and latter wire-frame image vegetarian refreshments forming short side.When last wire-frame image vegetarian refreshments with Initial profile pixel is connected after forming short side, can form a contour curve for closing.In certain embodiments, it is interested Region may be located at an inside for the contour curve of closing.For example, the area-of-interest of model entrance 740 (that is, enters in Fig. 7 The region of row mesh generation) it is located at the inside of contour curve.In certain embodiments, area-of-interest can be located at two envelopes Region between the contour curve for closing.For example, area-of-interest can be a two-dimentional cyclic structure, or with two-dimentional ring-type knot The structure of structure homeomorphic.The information (for example, the corresponding grid curve in region) in one or more regions can be stored in one Or in multiple storage devices (for example, storage device 130, memory module 260 etc.).The information in one or more regions can be Used by mess generation unit 540 or other units/modules that can carry out data analysis in follow-up process.

In 808, can whether a region be needed to carry out mesh generation to judge.In certain embodiments, institute Stating judgement can be realized by judging unit 580.After determining the region and need not carry out mesh generation, flow 800 enters 810.After determining the region and needing to carry out mesh generation, flow 800 enters 812.In certain embodiments, judging unit 580 conditions for being judged can be whether the region is area-of-interest.When the region is area-of-interest, then it is determined To need to carry out mesh generation.As described in elsewhere, area-of-interest can include needing into promoting circulation of blood in present disclosure book Liquid status analysis region, for example, in particular blood vessel blood flow region.

In 810, the region can be marked.In certain embodiments, the mark to region can be given birth to by grid Implement into unit 540.Mark can be in the form of the code of embodied on computer readable or executable instruction.Labeled area Domain information can be stored in one or more storage devices (for example, storage device 130, memory module 260 etc.).Labeled Area information can in follow-up process by mess generation unit 540 or other can carry out the units/modules of data analysis Read, so as to reject the labeled region when mesh generation is carried out.

In 812, mesh generation can be carried out to the region.In certain embodiments, mesh generation can be given birth to by grid Implement into unit 540.In certain embodiments, grid divide can be based on the region profile point carry out.The division of grid Algorithm includes triangulation, and corner mesh generation, hexagonal gridding is divided, or similar, or the group of one or more Close.Exemplary reseau-dividing algorithm includes Loop algorithms, butterfly-type algorithm of subdivision, Catmull-Clark algorithms, Doo-Sabin Algorithm, Delaunay triangle division algorithms etc..As just citing, mess generation unit 540 can utilize Delaunay triangles Divide (Delaunay triangulation) algorithm carries out mesh generation to all profile points in the region.Again for example, grid The profile point in the region first can be divided into different subsets by generation unit 540, and carry out mesh generation to each subset profile point. Then, the mesh generation of each subset can be merged mess generation unit 540 mesh generation to form the region.Specifically, The all of profile point in the region can be ranked up according to x/y coordinates (for example, non-decreasing sequence first is carried out according to x coordinate, it is right In x coordinate identical point, sorted according to y-coordinate non-decreasing).Profile point after sequence is divided into subset A and subset according to quantity B, and it is respectively completed Delaunay triangle divisions.The Delaunay triangle divisions of subset A and subset B are merged into all profiles again The Delaunay triangle divisions of point.In certain embodiments, mesh generation can also include by the contour curve in the region with it is logical The grid for crossing partitioning algorithm division is overlapped, so as to retain the contour curve in the region (for example, in 806 in the grid for dividing That mentions is connected one or more short sides for being formed by wire-frame image vegetarian refreshments).

In certain embodiments, can be using the mess generation method of concurrent technique to dividing for the grid in region. For example, application region divides or is similar to algorithm is divided into some sub-regions by the region, net is independently carried out in every sub-regions Lattice are divided, then repair the boundary mesh in adjacent subarea domain, and then obtain the complete grid in the region.

In 814, mesh generation control condition can be set to the region.In certain embodiments, mesh generation control The setting of condition can be realized by mess generation unit 540.Mesh generation control condition can control the quantity of grid, size, Distribution, shape, or similar, or the combination of one or more.In certain embodiments, mess generation unit 540 can be with One area-constrained condition of grid cell is set so that the area of arbitrary mess unit meets the area-constrained condition.For example, Mess generation unit 540 can set an area-constrained value so that the area of arbitrary mess unit is all not more than the area about Beam value.In certain embodiments, mess generation unit 540 can set an interior angle constraints for grid cell so that appoint The interior angle of meaning grid cell all meets the interior angle constraints.For example, mess generation unit 540 can set a triangle gridding The interior angle binding occurrence of unit so that the Minimum Internal Angle of any triangle gridding unit is all not less than the interior angle binding occurrence.In some realities Apply in example, mesh generation control condition can be by user by, for example, interactive device 140 is obtained after input.Mesh generation control Condition processed can also by mess generation unit 540 or other there are the units/modules of data analysis function according to specified conditions Analysis is obtained.Specified conditions can include the time that generation grid needs, and the quantity of the grid of generation, the grid according to generation enters The time that row model is calculated, levels of precision of result that the grid computing according to generation is obtained etc..

In 816, it can be determined that whether the grid of division meets control condition.In certain embodiments, to mesh generation Judgement can be completed by mess generation unit 540.If the grid for dividing is unsatisfactory for control condition, flow 800 enters 818。

In 818, grid can be processed.In certain embodiments, the treatment to grid can be by mess generation Unit 540 is completed.Grid treatment can include adjustment number of grid, and one or more are operated to change sizing grid etc..Adjustment net Lattice quantity can include improving mesh-density, reduce mesh-density etc..Changing sizing grid can include segmentation grid, merge net Lattice, recombinate etc. to grid.

In certain embodiments, if a triangle gridding unit is unsatisfactory for area-constrained condition (for example, the triangle gridding The area of unit is more than area-constrained value), then can insert one or more auxiliary magnets in the triangle gridding unit.Auxiliary magnet Insertion can be random, it is also possible to according to former triangle gridding characteristic point position insert.Mess generation unit 540 can be with New grid is generated according to auxiliary magnet.For example, can be in the inside of triangle gridding unit, for example, an auxiliary is inserted in center of gravity Point.The summit of connection auxiliary magnet and former triangle gridding can generate three new triangle gridding units.Again for example, can be in triangle Grid cell internal random ground inserts multiple auxiliary magnets with nonrandomness.Delaunay is utilized according to multiple auxiliary magnets Triangle division (Delaunay triangulation) algorithm partition goes out Delaunay triangulation network lattice.In certain embodiments, such as Really a triangle gridding unit is unsatisfactory for interior angle constraints, then can using specific algorithm to triangle gridding unit at Reason.It is for instance possible to use flip algorithms update triangle gridding unit.Specifically, flip algorithms can be included by selecting one Comprising two quadrangles of adjacent triangle gridding unit, (diagonal of quadrangle is that two triangle gridding units are adjacent Side), another diagonal is used as two sides of new triangle in selecting the quadrangle), obtain two new triangle gridding units. Interior angle constraints can include that the Minimum Internal Angle of triangle gridding unit is not less than an interior angle binding occurrence.Interior angle binding occurrence can be with It is 5 °, 10 °, 15 °, 20 °, 25 °, or other numerical value.

Grid returns to 816 after treatment, judges whether the grid after treatment meets control by mess generation unit 540 Condition processed.Until grid meets control condition, then flow 800 enters 820.

820, mess generation unit 540 can decide whether to have stepped through all regions.If it is not, then flow 800 is returned 808 are returned to, the judgement to being made whether grid division without the region for processing.If all regions are had stepped through, 822 In, the grid of area-of-interest is generated by mess generation unit 540.In certain embodiments, the grid class of different zones is divided The algorithm of type can be with identical or different.For example, all regions can all use Delaunay triangle division algorithm partition grids. Again for example, a part of region can use Delaunay triangle division algorithm partition grids, a part of region can use corner Reseau-dividing algorithm or hexagonal gridding partitioning algorithm carry out mesh generation.In certain embodiments, the grid of different zones is drawn Point control condition can be with identical or different.For example, the mesh generation control condition in all regions can include area-constrained condition And/or interior angle constraints.The area-constrained condition and/or interior angle constraints of different zones can be with identical or different.Specifically Ground, the interior angle constraints in all regions can be that the Minimum Internal Angle of any triangle gridding is not less than an interior angle binding occurrence (example Such as, 20 °).Again for example, the area-constrained condition of brain image can include that the area of maximum triangle gridding unit is not more than A, blood The area-constrained condition of pipe image can include that the area of maximum triangle gridding unit is not more than B, and wherein A is less than B.

Description above is only specific embodiment of the invention, is not considered as unique embodiment.Clearly for For one of skill in the art, after understand present invention and principle, all may be without departing substantially from the principle of the invention, structure In the case of, carry out various amendments and the change in form and details.In certain embodiments, 810 can be skipped.For example, such as Really a region is judged as that mesh generation need not be carried out, then can directly delete the region.In certain embodiments, 814 Before 808 being moved on to, i.e., mess generation unit 540 can to the region of grid division in need identical grid be set draw Divide control condition.In certain embodiments, flow 800 can carry out mesh generation to 3-D view.For example, to 3D region Mesh generation can be using the ball filling method (ball-packing) of quick Delaunay.Mess generation unit 540 can be three Layouted with ball filling method in dimension geometric areas, density conjunction is adaptively distributed according to the geometric properties and spatial relationship of geometrical model Suitable node, then using quick Delaunay insertion technology generation three-dimensional grids.

Basic conception is described above, it is clear that to those skilled in the art, foregoing invention is disclosed only As an example, and not constituting the restriction to the application.Although do not clearly state herein, those skilled in the art may Various modifications, improvement and amendment are carried out to the application.Such modification, improvement and amendment are proposed in this application, so such Change, improve, correct the spirit and scope for still falling within the application example embodiment.

Meanwhile, the application describes embodiments herein using particular words.Such as " one embodiment ", " one implements Example ", and/or " some embodiments " mean a certain feature related to the embodiment of the application at least one, structure or feature.Cause This, it should be highlighted that and it is noted that " embodiment " or " implementation that are referred to twice or repeatedly in diverse location in this specification Example " or " alternate embodiment " are not necessarily meant to refer to same embodiment.Additionally, in one or more embodiments of the application Some features, structure or feature can carry out appropriate combination.

Additionally, it will be understood by those skilled in the art that each side of the application can be by some with patentability Species or situation are illustrated and described, including any new and useful operation, machine, product or material combination, it is or right Their any new and useful improvement.Correspondingly, the various aspects of the application can completely by hardware perform, can be complete Performed by software (including firmware, resident software, microcode etc.), can also be performed by combination of hardware.Hardware above is soft Part is referred to alternatively as " data block ", " module ", " engine ", " unit ", " component " or " system ".Additionally, each side of the application The computer product being located in one or more computer-readable mediums may be shown as, the product includes computer-readable program Coding.

Computer-readable signal media may include a propagation data signal for being contained within computer program code, for example In base band or as a part for carrier wave.The transmitting signal may have many forms, including electromagnetic form, light form etc. Deng or suitable combining form.Computer-readable signal media can be any meter in addition to computer-readable recording medium Calculation machine computer-readable recording medium, the medium can by being connected to instruction execution system, device or an equipment realizing communicating, propagate or Transmit the program for using.Program coding in computer-readable signal media can be carried out by any suitable medium Propagate, including radio, cable, fiber optic cables, RF or similar mediums or any of above medium combination.

Computer program code needed for the operation of the application each several part can use any one or more programming language, Including Object-Oriented Programming Language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python etc., conventional procedural programming language for example C language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming language such as Python, Ruby and Groovy, or other programming languages etc..The program coding can be with complete It is complete to run on the user computer or run on the user computer as independent software kit or part is in subscriber computer Run on remote computer or server in remote computer operation or completely upper operation part.In the latter cases, remotely Computer can be connected by any latticed form with subscriber computer, such as LAN (LAN) or wide area network (WAN), or even Outer computer (such as by internet) is connected to, or in cloud computing environment, or it is service to use software such as service (SaaS)。

Additionally, except clearly stating in non-claimed, the order of herein described processing element and sequence, digital alphabet Using or other titles use, be not intended to limit the order of the application flow and method.Although by each in above-mentioned disclosure Kind of example discusses some it is now recognized that useful inventive embodiments, but it is to be understood that, such details only plays explanation Purpose, appended claims are not limited in the embodiment for disclosing, conversely, claim is intended to, and covering is all to meet the application The amendment of embodiment spirit and scope and equivalent combinations.For example, although system component described above can be set by hardware It is standby to realize, but only can also be achieved by the solution of software, pacify such as on existing server or mobile device The described system of dress.

Similarly, it is noted that in order to simplify herein disclosed statement, so as to help real to one or more inventions Apply the understanding of example, above to the description of the embodiment of the present application in, sometimes by various features merger to one embodiment, accompanying drawing or In descriptions thereof.But, this disclosure method be not meant to the application object required for aspect ratio claim in carry And feature it is many.In fact, the feature of embodiment will be less than whole features of the single embodiment of above-mentioned disclosure.

Description composition, the numeral of number of attributes are used in some embodiments, it should be appreciated that such for embodiment The numeral of description, has used qualifier " about ", " approximate " or " generally " etc. to modify in some instances.Unless said in addition Bright, " about ", " approximate " or " generally " shows that the numeral allows ± 20% change.Correspondingly, in some embodiments In, the numerical parameter used in description and claims is approximation, approximation feature according to needed for separate embodiment Can change.In certain embodiments, numerical parameter is considered as the significant digit of regulation and using the reservation of general digit Method.Although for confirming the Numerical Range and parameter of its scope range being approximation in the application some embodiments, specific real Apply in example, being set in for such numerical value is reported as precisely as possible in feasible region.

Finally, it will be understood that embodiment described herein is only used to illustrate the principle of the embodiment of the present application.Other Deformation be likely to belong to scope of the present application.Unrestricted accordingly, as example, the alternative configuration of the embodiment of the present application is visual It is consistent with teachings of the present application.Correspondingly, embodiments herein is not limited only to the implementation that the application is clearly introduced and described Example.

Claims

1. a kind of gridding processing method of medical image, methods described includes：

Extract multiple profile points of one or more of area-of-interests；

Based on a second mesh generation control condition, the grid of the second area is generated, wherein, second mesh generation Control condition is different from the first mesh generation control condition；And

One or more of area-of-interests are carried out by the grid of grid and the second area according to the first area Analysis.

2. method according to claim 1, one or more of area-of-interests include coronary artery, abdominal artery, At least one of arteriae cerebri, brain or artery of lower extremity.

3. the grid of method according to claim 1, the grid of the first area or the second area is based on Delaunay Triangulation algorithm is generated.

4. method according to claim 1, the first mesh generation control condition includes a first area-constrained bar Part.

5. method according to claim 4, the first area-constrained condition includes that the area of all grids is less than or waits In an area-constrained value.

6. method according to claim 4, the second mesh generation control condition includes a second area constraint bar Part, wherein, the second area constraints is different from the described first area-constrained condition.

7. method according to claim 1, further includes to determine the 3rd region according to the multiple profile point, its In, the 3rd region does not carry out mesh generation.

8. method according to claim 1, the analysis is carried out to the area-of-interest including according to calculating fluid force Learn the kinetic parameter that (CFD) analyzes the area-of-interest.

9. method according to claim 1, further includes：

The grid of grid and the second area according to the first area, generation corresponds to three of the 3-D view Dimension grid.

10. a kind of gridding processing system of medical image, the system includes：

One receiver module, is configured as：

One multidate feature generation module, is configured as：

Extract multiple profile points of one or more of area-of-interests；

A kind of 11. medical image network processing methods, methods described includes：

Obtain the image and an image for the second phase of first phase；

First angiosomes is selected in the image of the first phase, wherein, first angiosomes includes one Blood vessel；

Second angiosomes is selected in the image of second phase, wherein, second angiosomes is comprising at least A part of blood vessel；

Gridding treatment is carried out according to the method for claim 1 to first vascular pattern and second vascular pattern；

According to the boundary condition of first vascular pattern, determine that blood vessel is at described first described in first vascular pattern The state of phase；

Based on the blood vessel in the state of the first phase, first vascular pattern and second vascular pattern are associated, First vascular pattern and second vascular pattern of associating includes grid and the institute of matching first vascular pattern State the grid of the second vascular pattern；And

According to the association results and the boundary condition of second vascular pattern, determine described in second vascular pattern State of the blood vessel in second phase.

Method described in 12. claims 11, methods described includes：

Side wall to first vascular pattern carries out gridding treatment；And

Gridding result based on the entrance, outlet and side wall, carries out three dimensional network and formats to first vascular pattern Treatment.

Method described in 13. claims 11, methods described includes：

Side wall to second vascular pattern carries out gridding treatment；And

Gridding result based on the entrance, outlet and side wall, carries out three dimensional network and formats to second vascular pattern Treatment.

14. 1 gridding processing systems of medical image, the system includes：

At least one processor；And

Memory, for store instruction, when the instruction is by least one computing device, causes what the system was realized Operation includes：

Extract multiple profile points of one or more of area-of-interests；