CN108735270A - Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model - Google Patents

Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model Download PDF

Info

Publication number
CN108735270A
CN108735270A CN201810516585.0A CN201810516585A CN108735270A CN 108735270 A CN108735270 A CN 108735270A CN 201810516585 A CN201810516585 A CN 201810516585A CN 108735270 A CN108735270 A CN 108735270A
Authority
CN
China
Prior art keywords
coronary artery
blood flow
dimensionality reduction
cross
reduction model
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201810516585.0A
Other languages
Chinese (zh)
Inventor
李长岭
董樑
孙勇
夏永清
冷晓畅
向建平
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Pulse Flow Technology Co Ltd
Original Assignee
Hangzhou Pulse Flow Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hangzhou Pulse Flow Technology Co Ltd filed Critical Hangzhou Pulse Flow Technology Co Ltd
Priority to CN201810516585.0A priority Critical patent/CN108735270A/en
Publication of CN108735270A publication Critical patent/CN108735270A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis

Abstract

The invention discloses blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model, wherein method includes:Step S1 obtains and handles coronary artery medical image, obtains the dimensionality reduction model of expression coronary artery geometry topological structure, and the dimensionality reduction model includes the cross-sectional area of center line vector sum coronary artery coronarius everywhere;Step S2 obtains coronary artery related physiological parameters, and resistance coefficient of the coronary artery to blood flow is calculated according to dimensionality reduction model;Step S3, according in coronary artery blood flow flow and the resistance coefficient, calculate pressure value everywhere in coronary artery;The blood flow reserve score of corresponding position is calculated based on the pressure value in coronary artery everywhere in step S4.The present invention establishes the dimensionality reduction model of coronary artery using coronary artery medical image, obtains blood flow reserve score in real time according to Hemodynamics calculating, while ensureing accuracy, greatly improves operation efficiency.

Description

Blood flow reserve score acquisition methods, device, system and computer based on dimensionality reduction model Storage medium
Technical field
The present invention relates to field of medical technology, and in particular to a kind of blood flow reserve based on coronary artery dimensionality reduction model Score acquisition methods, device, system and computer storage media.
Background technology
The main reason for atherosclerosis is coronary heart disease, cerebral infarction and peripheral vascular disease seriously affects the body of people Body Health and Living quality.For hat venereal disease diagnosis, angiography of coronary arteries is considered as " goldstandard ", but this Method can only evaluation of vascular diseases become position stenosis, can not influence of the quantitative assessment hemadostewnosis to physiological function, may Over-evaluate the severity for either underestimating lesion and then over-treatment or lesion is caused not to handle.Present medical diagnosis is coronal The generally acknowledged index of arteriarctia is blood flow reserve score (FFR), and the definition of blood flow reserve score is:In coronary artery, there are narrow In the case of lesion, the distal vessels of the coronary artery stenosis lesion can be obtained maximum blood flow and when institute under normal condition The ratio of obtainable maximum blood flow.
In the prior art, generally use intrusive mood is tested to obtain FFR, for example, diagnostic cardiac catheterization, performed the operation Journey includes:Conventional angiography of coronary arteries (CCA) is carried out so that coronary artery pathological changes visualize, while intravenously using gland Glycosides induction (coronary artery be in maximum congestive state), calculate the coronary artery stenosis distal end pressure that is obtained by pressure transducer with The ratio of heart aorta pressure determines FFR.Intrusive mood test can cause patient body wound, increase operation risk and control Treatment expense.
The risk and expensive expense that intervention diagnosis is brought can be then avoided by numerical simulation calculation FFR, carry out Numerical-Mode When quasi- calculating, patient data (such as CT, MRI, DSA etc.) is acquired by high-definition image equipment first, then to patient vessel's mould Type is reconstructed, and carrys out the blood flow situation in simulated blood vessel in conjunction with Fluid Mechanics Computation (CFD) method.According to clinical data pair Than noninvasive FFR is highly effective to the diagnosis of myocardial ischemia, while also more more acurrate than imaging evaluation.
In general, the calculating of non-intrusion type blood flow reserve score is carried out based on threedimensional model, the blood of blood vessel regional area is studied Stream needs the solution for carrying out flow equation to the element of volume in whole region to integrate after solving convergence and extract required pressure The information such as power distribution, taking can be longer.
Invention content
The blood flow reserve score acquisition methods that the present invention provides a kind of based on coronary artery dimensionality reduction model, device and System establishes the dimensionality reduction model of coronary artery using coronary artery medical image, and real-time obtain is calculated according to Hemodynamics To blood flow reserve score operation efficiency is greatly improved while ensureing accuracy.
A method of blood flow reserve score is obtained based on coronary artery dimensionality reduction model, including:
Step S1 obtains and handles coronary artery medical image, obtains the dimensionality reduction of expression coronary artery geometry topological structure Model, the dimensionality reduction model include the cross-sectional area of center line vector sum coronary artery coronarius everywhere;
Step S2 obtains coronary artery related physiological parameters, and calculates coronary artery to blood flow according to dimensionality reduction model Resistance coefficient;
Step S3, according in coronary artery blood flow flow and the resistance coefficient, calculate in coronary artery everywhere Pressure value;
The blood flow reserve score of corresponding position is calculated based on the pressure value in coronary artery everywhere in step S4.
The coronary artery medical image includes but not limited to using CT (i.e. CT scan), MRI (i.e. magnetic Resonance image-forming), DSA (i.e. Digital subtraction angiograph) obtain image, can obtain coronarius three according to these images Tie up structural information.
Include still three dimensions geological information coronarius in heretofore described dimensionality reduction model, but by coronary artery Each branch be reduced to one-dimensional linear structure, to improve the computational efficiency of blood flow reserve score.
Connection relation and space bit between each branch of coronary artery can be obtained according to center line vector coronarius Relationship is set, skeleton structure coronarius is obtained.
In step S2, the coronary artery moves towards the resistance coefficient of blood flow and the angle of vascular bifurcation center line, Centerline length between the cross-sectional area of blood vessel and two bifurcations is related, and the prior art can be used in calculating process.
In step S3, prior art acquisition may be used in the blood flow flow in coronary artery, for example, being surveyed using Doppler method Amount arteria carotis communis volume flow rate and colored quantitative velocity imaging (CVI-Q) method measure.
The center line vector is the vector of each main coronary artery of characterization and the center line of branch, according to center line to Amount can obtain the space trend of main coronary artery and branch.
Coronary artery medical image and coronary artery related physiological parameters can obtain simultaneously, non-concurrent can also obtain. The coronary artery related physiological parameters include at least physiological parameter involved in calculating process, including but not limited to:Physiology Medical test results (such as:Cardiac cycle, blood pressure, blood flow, hemoglobin, blood platelet, electrocardiogram, gene, family's medical history etc. Deng), image data/segmentation data/reconstruct geometric data (narrow location, narrow length, stenosed section, calcified plaque, heart ruler It is very little, coronary arterial tree and topological structure etc.).
A variety of methods may be used in the structure of the dimensionality reduction model, and one of which is suitable for CT (i.e. electronic computer tomographies Scanning), MRI (i.e. magnetic resonance imaging), the method for DSA (i.e. Digital subtraction angiograph) image it is as follows:
The construction method of the dimensionality reduction model, including:
Step S1-1-1, chooses entrance coronarius as initial position in the coronary artery medical image, Initial position obtains the cross section of coronary artery inlet, using the geometric center of gravity of cross section as the central point of the cross section, Two orthogonal feature vectors are determined using central point as origin, the friendship according to two feature vectors and coronary artery periphery Point determines initial position cross-sectional area coronarius;
Step S1-1-2, along the direction both perpendicular to two feature vectors, with two features of pre- fixed step size synchronous translational Vector determines the transversal of corresponding position coronary artery cross section according to the intersection point of two feature vectors and coronary artery periphery Area, using the geometric center of gravity of cross section as the central point of coronary artery cross section at this;
Step S1-1-3 determines bifurcation coronarius according to the changing value of cross-sectional area, at two bifurcations Center position determine center line vector, establish according to center line vector sum coronary artery cross-sectional area everywhere described in Dimensionality reduction model.
Preferably, in step S1-1-1 and step S1-1-2, coronary artery periphery is obtained using edge detection, at two On the direction of feature vector, the diameter of coronary artery periphery is respectively d2And d3, rp=(d2+d3)/4, d2And d3The center of circle overlap By coronary artery periphery be approximately using point O it is the center of circle with r for point OpCross-sectional area is calculated for the circle of radius.
Preferably, in step S1-1-3, if it is determined that factor g > 1.9, then be coronal between cross section at coronary artery two The bifurcation of artery, judgement factor g=max { d2, d3}/min{d2, d3}。
Another kind is suitable for CT (i.e. CT scan), MRI (i.e. magnetic resonance imaging), DSA (i.e. digital outline Angiography) image dimensionality reduction model construction method it is as follows:
The construction method of the dimensionality reduction model, including:
Step S1-2-1 pre-processes the coronary artery medical image, obtains binary image;
Step S1-2-2 carries out micronization processes to binary image, obtains center line vector coronarius;
Step S1-2-3 traverses coronary artery along the center line vector, using center line everywhere unit vector as transversal The normal vector in face does cross section to coronary artery, and the boundary of coronary artery cross section is determined according to gray threshold, to cross section into Row integral obtains the cross-sectional area of coronary artery corresponding position, according to the cross section of the center line vector sum coronary artery everywhere Product establishes the dimensionality reduction model.
Preferably, in step S1-2-1, the coronary artery medical image includes multiple two dimensional gray distribution maps, according to Slice is ranked sequentially each image, and following processing is done for each image:
Step S1-2-1-1 is based on the corresponding substrate image of each image creation, and each region has difference in substrate image Gray threshold;
Step S1-2-1-2 carries out binary conversion treatment to corresponding projected image using substrate image, obtains projected image Binary image;
Step S1-2-1-3 builds the binary picture of coronary artery medical image using the binary image of each image Picture.
The present invention also provides a kind of computer readable storage medium, the computer-readable recording medium storage has calculating Machine program, the computer program are subsequently can by computer being obtained based on coronary artery dimensionality reduction model described in realization when device executes The method for taking blood flow reserve score.
The present invention also provides a kind of devices obtaining blood flow reserve score, including computer storage, computer disposal Device and it is stored in the computer program that can be executed in the computer storage and on the computer processor, it is described When computer processor executes the computer program, realizes and described blood flow storage is obtained based on coronary artery dimensionality reduction model The method of back-up number.
The present invention also provides a kind of system obtaining blood flow reserve score, including terminal and server, the services Device includes computer storage, computer processor and is stored in the computer storage and can be in the computer The computer program executed on processor, the server obtains coronary artery medical image from terminal and coronary artery is related Physiological parameter;When the computer processor executes the computer program, the side of the acquisition blood flow reserve score is realized Method.
The terminal and server is communicated by wired or wireless way, and the terminal is usually provided at medical services machine Structure can upload coronary artery medical image by terminal to server, and the server is generally arranged at third party's service machine Structure carries out analyzing processing to coronary artery medical image, obtains blood flow reserve score and feed back to terminal, is medical treatment patient The diseases such as myocardial ischemia provide fast and accurately foundation.
The software section of terminal and server uses C, C++, Java, the exploitation of the programming languages such as Pyho, HTM5 to complete.
Blood flow reserve score acquisition methods provided by the invention based on coronary artery dimensionality reduction model, device and it is System establishes the dimensionality reduction model of coronary artery using coronary artery medical image, is obtained in real time according to Hemodynamics calculating Blood flow reserve score, while ensureing accuracy, the CPU calculating times are about reduced to 1/10th needed for the prior art.
Description of the drawings
Fig. 1 is that the present invention is based on the flow charts of the blood flow reserve score acquisition methods of coronary artery dimensionality reduction model;
In Fig. 2, (a) is coronary artery medical image, is (b) coronary artery figure;(c) coronary artery dimensionality reduction model;
Fig. 3 is to be established in dimensionality reduction model process in embodiment 1, the position relationship of two feature vectors and coronary artery Schematic diagram;
Fig. 4 is coronary artery overall network figure;
Fig. 5 is the blood flow profile of flowrate of a cardiac cycle, as coronary artery inlet blood under different HR Heart Rates The input value of flow velocity degree;
Fig. 6 is the model schematic of coronary artery stenosis.
Specific implementation mode
Below in conjunction with the accompanying drawings, to the present invention is based on the blood flow reserve score acquisition methods of coronary artery dimensionality reduction model and System is described in detail.
Embodiment 1
As shown in Figure 1, a kind of method that blood flow reserve score is obtained based on coronary artery dimensionality reduction model, including:
Step S1 obtains and handles coronary artery medical image, obtains the dimensionality reduction of expression coronary artery geometry topological structure Model, the dimensionality reduction model include the cross-sectional area of center line vector sum coronary artery coronarius everywhere.
Coronary artery medical image includes but not limited to using CT (i.e. CT scan), MRI (i.e. magnetic resonance Imaging), the images that obtain of DSA (i.e. Digital subtraction angiograph), it is four-dimensional that expression-form is not limited to two dimension, three peacekeepings, according to being preced with Shape artery medical image can obtain three-dimensional structure information coronarius, the image data lattice of coronary artery medical image Formula is not limited to Dicom files.
As shown in Fig. 2, (a) is three-dimensional coronary artery medical image in Fig. 2, it is (b) coronary artery figure;(c) coronal dynamic Arteries and veins dimensionality reduction model.Include the spatial relation of each branch of coronary artery in dimensionality reduction model coronarius, but will be coronal dynamic Each branch of arteries and veins is reduced to one-dimensional linear structure, i.e., the position of each bifurcation and spatial relation and is moved with coronal in figure (a) Bifurcation information is consistent in arteries and veins medical image, reaches branch using single line segment table between two neighboring bifurcation.
The blood vessel volume elements of the brightness ratio of cholesterol plaques is much bigger, in order to improve the accuracy of dimensionality reduction model construction, into Before the structure of row dimensionality reduction model, cholesterol plaques are blocked.
The construction method of dimensionality reduction model, including:
Step S1-1-1, chooses entrance coronarius as initial position in the coronary artery medical image, Initial position obtains the cross section of coronary artery inlet, using the geometric center of gravity of cross section as the central point of the cross section, Two orthogonal feature vectors are determined using central point as origin, the friendship according to two feature vectors and coronary artery periphery Point determines initial position cross-sectional area coronarius.
The profile of coronary artery periphery namely vascular wall coronarius, on coronary artery medical image, coronary artery Vascular wall has significant change compared to other regional luminances, and coronary artery circumferential position can be obtained by detecting brightness change.
As shown in figure 3, two orthogonal feature vectors are respectively v2And v3, on the direction of two feature vectors, hat The diameter of shape periarterial is respectively d2 and d3, rpIt is point O that the center of circle of=(d2+d3)/4, d2 and d3, which overlaps, will be outside coronary artery It is the center of circle with r that week, which is approximately using point O,pCross-sectional area is calculated for the circle of radius.
Step S1-1-2, along the direction both perpendicular to two feature vectors, with two features of pre- fixed step size synchronous translational Vector determines the transversal of corresponding position coronary artery cross section according to the intersection point of two feature vectors and coronary artery periphery Area, using the geometric center of gravity of cross section as the central point of coronary artery cross section at this.
Both perpendicular to the direction of two feature vectors, i.e. vector v in figure1Indicated direction, vector v1Instruction direction It is consistent with extending direction coronarius.Along vector v1Direction with two feature vectors of pre- fixed step size synchronous translational, such as just Beginning position is position 1, after pre- fixed step size synchronous translational, in-position 2 and position 3 successively, and respectively at position 2 and position 3, Calculate the central point and cross-sectional area of corresponding coronary artery cross section.
The geometric center of gravity of cross section is the central point of cross section, and the algorithm of cross-sectional area is referring to the transversal of initial position Face algorithm.
The more short then counting accuracy of pre- fixed step size is higher, and pre- fixed step size more long then operation time is shorter, actual predetermined step Long tradeoff computational accuracy and operation time obtain.
Pre- fixed step size can select as needed, may be the same or different at different zones, for example, coronal The larger crooked position of artery curvature, the shorter pre- fixed step size of setting;In the smaller crooked position of coronary artery curvature, setting compared with Long pre- fixed step size.
Step S1-1-3 determines bifurcation coronarius according to the changing value of cross-sectional area, at two bifurcations Center position determine center line vector, establish dimensionality reduction mould according to the cross-sectional area of center line vector sum coronary artery everywhere Type.
In the present embodiment, it is first determined then bifurcation coronarius obtains branch vessel by starting point of bifurcation Center line and cross-sectional area (the step of obtaining center line and cross-sectional area with main coronary artery blood vessel (i.e. step S1-1- 1) equally).
According on two feature vector directions, diameter calculation coronarius judges factor g, judgement factor g=max { d2, d3}/min{d2, d3, if it is determined that factor g > 1.9, then be bifurcation coronarius between cross section at coronary artery two,
Step S2 obtains coronary artery related physiological parameters, and calculates coronary artery to blood flow according to dimensionality reduction model Resistance coefficient.
Step S3 calculates blood everywhere in coronary artery according to the blood flow flow and resistance coefficient in coronary artery Pressure value.
Coronary artery includes to the resistance coefficient of blood flow:Resistance coefficient at coronary artery bifurcation, and Resistance coefficient between two bifurcations, the calculating of resistance coefficient is referring to document:Chnafa C,Valen-Sendstad K,Brina O,et al.Improved reduced-order modelling of cerebrovascular flow distribution by accounting for arterial bifurcation pressure drops[J].Journal of biomechanics,2017,51:83-88。
The main process of step S2 and step S3 includes:
First, each branch in coronary artery dimensionality reduction model is divided into several segmentations, fluid is established for each segmentation Governing equation and boundary control equations, it is as follows respectively:
Fluid governing equation:
In formula:Sk:The vascular cross-section product being segmented for k-th;
uk:The mean blood flow velocity being segmented for k-th;
ρ:For blood flow density;
Indicate external force, such as gravity, frictional force etc. suffered by blood vessel;
x:Indicate disalignment distance;
t:Indicate the time.
Boundary control equations:
pk:Indicate the pressure p on k-th of segmented vessel;
ρ:Blood flow density;
ck:Indicate the blood vessel elasticity modulus of k-th of segmentation, rule of thumb formula obtains;
f(Sk):It indicates and the relevant specific function of vascular cross-section.
Equation (1) (2) (3) is referring to document:T.M.Gamilov,P.Kopylov,R.Pryamonosov,S.Simakov, Virtual fractional flow reserve assessment in patient-specific coronary networks by 1D hemodynamic model,Russ.J.Numer.Anal.Math.Modelling 2015;30(5): 269–276。
The resistance R of blood flow branch section (i.e. branch between two bifurcations)kCome from:The resistance that blood flow is generated along blood flow Force coefficient R1With the resistance coefficient R of coronary arterial tree2, specifically, for the blood vessel containing branch, resistance coefficient Rk= R1+R2, for the blood vessel not comprising branch, resistance coefficient Rk=R1
In formula, R1The resistance coefficient generated along blood flow for blood flow;
μ is mean blood flow velocity;
LkFor the blood flow paths length of branch section;
Lk=∑si||δi|| (5)
δiFor the link vector of the i-th node and i+1 node of k-th of segmented vessel center line;
rkIt is the mean radius of branch section blood vessel:
δiFor the link vector of the i-th node and i+1 node of k-th of segmentation section vessel centerline;
riFor the radius of the blood vessel at node i.
In the resistance coefficient R that calculating blood flow is generated in coronary artery crotch2When, ρ is the density of blood flow, QdatAnd rdatPoint Not Wei branch blood flow flow and radius, angle of the upstream and downstream blood vessel at bifurcation is αDat, k
Equation (4) (5) (6) (7) (8) is referring to document:Chnafa C,Valen-Sendstad K,Brina O,et al.Improved reduced-order modelling of cerebrovascular flow distribution by accounting for arterial bifurcation pressure drops[J].Journal of biomechanics,2017,51:83-88。
When carrying out Dimension Reduction Analysis, according to two hypothesis:Blood flow flow is proportional to pressure, is inversely proportional to resistance coefficient, k-th The blood flow flow Q of segmentationkCalculation formula it is as follows:
Skuk=Qk (9)
By fluid governing equation (1) (2) and boundary control equations (3) can in the hope of the blood flow velocity μ of each segmentation of blood vessels, Then every section of blood vessel can be calculated in the hope of the blood flow of this segmented vessel by formula (4)-(8) by formula (9) Resistance Value.
The pressure drop Δ P of every section blood vessel can be finally calculated by formula (10)k, and then obtain the pressure of blood vessel everywhere Value.
Coronary artery overall network figure is as shown in figure 4, arterial blood enters coronary artery by left ventricle through aorta, in figure, RCA is arteria coronaria dextra, LCA is arteria coroaria sinistra, LCX is rami circumflexus arteriae coronariae sinistrae, LAD is ramus descendens anterior arteriae coronariae sinistrae, Each number refers to the number of coronary artery difference branch.
Under different HR Heart Rates, the blood flow profile of flowrate of a cardiac cycle is as shown in figure 5, in different HR Heart Rates Under, blood flow flow has variation, corresponding affects on the computational accuracy of FFR.
The calculating of blood flow flow uses the prior art, referring specifically to document I.E.Vignon-Clementel, C.A.Figueroa,K.E.Jansen and C.A.Taylor,Outflow boundary conditions for three- dimensional finite element modeling of blood flow and pressure in arteries, Computer Methods in Applied Mechanics and Engineering,195(29):3776-3796, 2006.。
The pressure value in coronary artery everywhere is calculated according to blood flow flow and resistance coefficient, using the prior art, tool Body is referring to document Byar D, Fiddian R V, Quereau M, et al.The fallacy of applying the Poiseuille equation to segmental arterial stenosis[J].American heart journal, 1965,70(2):216-224.。
The blood flow reserve score of corresponding position is calculated based on the pressure value in coronary artery everywhere in step S4.
The calculation formula of blood flow reserve score FFR is as follows:
In formula:PDista writing brushesFor the pressure value of narrow far downstream end;
PaorticFor the pressure value of narrow upstream proximal end.
For hemadostewnosis model as shown in fig. 6, under normal circumstances, it is 1 that blood flow upstream and downstream pressure, which does not have significant change, i.e. FFR, When occurring narrow in blood vessel, the pressure value of narrow far downstream end significantly reduces, and FFR is less than 1.
Embodiment 2
The present embodiment is difference from example 1 is that dimensionality reduction model building method, before building dimensionality reduction model, together Sample blocks cholesterol plaques.
The construction method of dimensionality reduction model, including:
Step S1-2-1 pre-processes coronary artery medical image, obtains binary image, specifically includes:
In step S1-2-1, the coronary artery medical image includes multiple two dimensional gray distribution maps, according to slice sequence Each image is arranged, following processing is done for each image:
Step S1-2-1-1 is based on the corresponding substrate image of each image creation, and each region has difference in substrate image Gray threshold;
Step S1-2-1-2 carries out binary conversion treatment to corresponding projected image using substrate image, obtains projected image Binary image;
Step S1-2-1-3 builds the binary picture of coronary artery medical image using the binary image of each image Picture.
Step S1-2-2 carries out micronization processes to binary image, obtains center line vector coronarius.
Step S1-2-3 traverses coronary artery along the center line vector, using center line everywhere unit vector as transversal The normal vector in face does cross section to coronary artery, and the boundary of coronary artery cross section is determined according to gray threshold, to cross section into Row integral obtains the cross-sectional area of coronary artery corresponding position, according to the cross section of the center line vector sum coronary artery everywhere Product establishes the dimensionality reduction model.
The determination process for not including bifurcation in the present embodiment, it is coronal by being obtained to binary image progress micronization processes The center line of artery major blood vessel and branch vessel vector, the center line vector are different from embodiment 1 between two bifurcations Vector, but (b) directly passes through the center knot that step S1-2-1, step S1-2-2 and step 1-2-3 are obtained from Fig. 2 Structure.
In addition to the building process of dimensionality reduction model, remaining step is the same as embodiment 1.
Embodiment 3
A kind of computer readable storage medium, the computer-readable recording medium storage have computer program, the meter Calculation machine program be subsequently can by computer device execute when realize as described in embodiment 1 or embodiment 2 based on coronary artery dimensionality reduction The method that model obtains blood flow reserve score.
Embodiment 4
It is a kind of to obtain the device of blood flow reserve score, including computer storage, computer processor and it is stored in institute The computer program that can be executed in computer storage and on the computer processor is stated, the computer processor executes When the computer program, realizes and blood flow is obtained based on coronary artery dimensionality reduction model as described in embodiment 1 or embodiment 2 The method for laying in score.
The present embodiment device is configurable on high in the clouds, obtains coronary artery image by the remote terminal being attached thereto, may be used also To be that the present embodiment device is inherently configured in terminal, directly obtained medical imaging device or by way of being manually entered coronal Artery image.
Embodiment 5
A kind of system obtaining blood flow reserve score, including terminal and server, the server include that computer is deposited It reservoir, computer processor and is stored in the computer storage and can be executed on the computer processor Computer program, the server obtain coronary artery medical image and coronary artery related physiological parameters from terminal;It is described When computer processor executes the computer program, the acquisition blood flow reserve score as described in embodiment 1 or embodiment 2 is realized Method.
According to the disclosure and teachings of the above specification, those skilled in the art in the invention can also be to above-mentioned embodiment party Formula carries out change and modification appropriate.Therefore, the invention is not limited in specific implementation modes disclosed and described above, to this Some modifications and changes of invention should also be as falling into the scope of the claims of the present invention.In addition, although this specification In used some specific terms, these terms are merely for convenience of description, does not limit the present invention in any way.

Claims (9)

1. a kind of method obtaining blood flow reserve score based on coronary artery dimensionality reduction model, which is characterized in that including:
Step S1 obtains and handles coronary artery medical image, obtains the dimensionality reduction model of expression coronary artery geometry topological structure, The dimensionality reduction model includes the cross-sectional area of center line vector sum coronary artery coronarius everywhere;
Step S2 obtains coronary artery related physiological parameters, and calculates resistance of the coronary artery to blood flow according to dimensionality reduction model Force coefficient;
Step S3, according in coronary artery blood flow flow and the resistance coefficient, calculate blood everywhere in coronary artery Pressure value;
The blood flow reserve score of corresponding position is calculated based on the pressure value in coronary artery everywhere in step S4.
2. the method for obtaining blood flow reserve score based on coronary artery dimensionality reduction model as described in claim 1, feature It is, the construction method of the dimensionality reduction model, including:
Step S1-1-1 chooses entrance coronarius as initial position, initial in the coronary artery medical image At position, the cross section of coronary artery inlet is obtained, using the geometric center of gravity of cross section as the central point of the cross section, in Heart point determines two orthogonal feature vectors as origin, according to the intersection point of two feature vectors and coronary artery periphery, Determine initial position cross-sectional area coronarius;
Step S1-1-2, along the direction both perpendicular to two feature vectors, with two feature vectors of pre- fixed step size synchronous translational, According to the intersection point of two feature vectors and coronary artery periphery, the cross-sectional area of corresponding position coronary artery cross section is determined, Using the geometric center of gravity of cross section as the central point of coronary artery cross section at this;
Step S1-1-3 determines bifurcation coronarius according to the changing value of cross-sectional area, at two bifurcations Heart point location determination center line vector, the dimensionality reduction is established according to the cross-sectional area of the center line vector sum coronary artery everywhere Model.
3. the method for obtaining blood flow reserve score based on coronary artery dimensionality reduction model as claimed in claim 2, feature It is, in step S1-1-1 and step S1-1-2, coronary artery periphery is obtained using edge detection, in the side of two feature vectors Upwards, the diameter of coronary artery periphery is respectively d2And d3, rp=(d2+d3)/4, d2And d3The center of circle overlap be point O, will be coronal It is the center of circle with r that periarterial, which is approximately using point O,pCross-sectional area is calculated for the circle of radius.
4. the method for obtaining blood flow reserve score based on coronary artery dimensionality reduction model as claimed in claim 2, feature It is, in step S1-1-3, if it is determined that factor g > 1.9, then be bifurcated coronarius between cross section at coronary artery two Point, judgement factor g=max { d2, d3}/min{d2, d3}。
5. the method for obtaining blood flow reserve score based on coronary artery dimensionality reduction model as described in claim 1, feature It is, the construction method of the dimensionality reduction model, including:
Step S1-2-1 pre-processes the coronary artery medical image, obtains binary image;
Step S1-2-2 carries out micronization processes to binary image, obtains center line vector coronarius;
Step S1-2-3 traverses coronary artery along the center line vector, using center line everywhere unit vector as cross section Normal vector does cross section to coronary artery, and the boundary of coronary artery cross section is determined according to gray threshold, is accumulated to cross section The cross-sectional area for getting coronary artery corresponding position is built according to the cross-sectional area of the center line vector sum coronary artery everywhere Found the dimensionality reduction model.
6. the method for obtaining blood flow reserve score based on coronary artery dimensionality reduction model as claimed in claim 5, feature It is, in step S1-2-1, the coronary artery medical image includes multiple two dimensional gray distribution maps, is ranked sequentially according to slice Each image does following processing for each image:
Step S1-2-1-1 is based on the corresponding substrate image of each image creation, and each region has different ashes in substrate image Spend threshold value;
Step S1-2-1-2 carries out binary conversion treatment to corresponding projected image using substrate image, obtains the two of projected image Value image;
Step S1-2-1-3 builds the binary image of coronary artery medical image using the binary image of each image.
7. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, feature to exist In the computer program, which is subsequently can by computer when device executes, realizes that claim 1~6 any one of them such as is based on coronal move The method that arteries and veins blood vessel dimensionality reduction model obtains blood flow reserve score.
8. a kind of device obtaining blood flow reserve score, including computer storage, computer processor and it is stored in described In computer storage and the computer program that can be executed on the computer processor, which is characterized in that the computer When processor executes the computer program, realize that claim 1~6 any one of them such as is based on coronary artery dimensionality reduction The method that model obtains blood flow reserve score.
9. a kind of system obtaining blood flow reserve score, including terminal and server, the server includes computer storage Device, computer processor and it is stored in the meter that can be executed in the computer storage and on the computer processor Calculation machine program, which is characterized in that the server obtains coronary artery medical image and coronary artery relevant physiological from terminal Parameter;When the computer processor executes the computer program, realize that claim 1~6 any one of them such as obtains The method of blood flow reserve score.
CN201810516585.0A 2018-05-25 2018-05-25 Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model Pending CN108735270A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810516585.0A CN108735270A (en) 2018-05-25 2018-05-25 Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810516585.0A CN108735270A (en) 2018-05-25 2018-05-25 Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model

Publications (1)

Publication Number Publication Date
CN108735270A true CN108735270A (en) 2018-11-02

Family

ID=63936090

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810516585.0A Pending CN108735270A (en) 2018-05-25 2018-05-25 Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model

Country Status (1)

Country Link
CN (1) CN108735270A (en)

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110120031A (en) * 2019-04-02 2019-08-13 四川锦江电子科技有限公司 A kind of method and apparatus obtaining vascular flow deposit score
CN111134651A (en) * 2019-12-09 2020-05-12 杭州脉流科技有限公司 Method, device and system for calculating fractional flow reserve based on intracavity images and computer storage medium
CN111161342A (en) * 2019-12-09 2020-05-15 杭州脉流科技有限公司 Method, device, equipment and system for obtaining fractional flow reserve based on coronary angiography image and readable storage medium
CN111227822A (en) * 2018-11-28 2020-06-05 苏州润心医疗器械有限公司 Coronary artery blood flow reserve fraction calculation method based on myocardial blood flow volume and CT image
CN111227821A (en) * 2018-11-28 2020-06-05 苏州润心医疗器械有限公司 Microcirculation resistance index calculation method based on myocardial blood flow and CT (computed tomography) images
CN112690814A (en) * 2020-11-06 2021-04-23 杭州阿特瑞科技有限公司 Low-error coronary artery blood flow reserve fraction measuring method
WO2021087967A1 (en) * 2019-11-04 2021-05-14 苏州润迈德医疗科技有限公司 Method and apparatus for acquiring blood vessel assessment parameter on basis of physiological parameter, and storage medium
CN112971818A (en) * 2021-01-28 2021-06-18 杭州脉流科技有限公司 Method and device for rapidly acquiring microcirculation resistance index, computer equipment and storage medium
CN113995388A (en) * 2021-12-13 2022-02-01 数坤(北京)网络科技股份有限公司 Fractional flow reserve calculation method and device, electronic equipment and readable storage medium
CN116109788A (en) * 2023-02-15 2023-05-12 张春阳 Method for modeling and reconstructing solid piece
CN116128864A (en) * 2023-02-22 2023-05-16 北京医准智能科技有限公司 Fractional flow reserve evaluation method, fractional flow reserve evaluation device, electronic equipment and storage medium
CN116636826A (en) * 2023-07-27 2023-08-25 深圳市爱保护科技有限公司 Training method and device of blood pressure estimation model, electronic equipment and storage medium

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101836235A (en) * 2007-08-16 2010-09-15 皇家飞利浦电子股份有限公司 Imaging method for sampling a cross-section plane in a three-dimensional (3d) image data volume
CN103300820A (en) * 2012-03-13 2013-09-18 西门子公司 Method and system for non-invasive functional assessment of coronary artery stenosis
US20160283684A1 (en) * 2014-03-28 2016-09-29 Jesse Israel Kinbarovsky System and method for providing audiovisual feedback
CN106651846A (en) * 2016-12-20 2017-05-10 中南大学湘雅医院 Method for segmenting vasa sanguinea retinae image
CN107133959A (en) * 2017-06-12 2017-09-05 上海交通大学 A kind of quick vessel borders three-dimensional dividing method and system
CN107427268A (en) * 2014-11-14 2017-12-01 西门子保健有限责任公司 Method and system for the blood flow reserve fraction based on pure geometry machine learning
CN107613874A (en) * 2015-03-31 2018-01-19 新加坡科技研究局 Method and apparatus for assessing hemadostewnosis

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101836235A (en) * 2007-08-16 2010-09-15 皇家飞利浦电子股份有限公司 Imaging method for sampling a cross-section plane in a three-dimensional (3d) image data volume
CN103300820A (en) * 2012-03-13 2013-09-18 西门子公司 Method and system for non-invasive functional assessment of coronary artery stenosis
US20160283684A1 (en) * 2014-03-28 2016-09-29 Jesse Israel Kinbarovsky System and method for providing audiovisual feedback
CN107427268A (en) * 2014-11-14 2017-12-01 西门子保健有限责任公司 Method and system for the blood flow reserve fraction based on pure geometry machine learning
CN107613874A (en) * 2015-03-31 2018-01-19 新加坡科技研究局 Method and apparatus for assessing hemadostewnosis
CN106651846A (en) * 2016-12-20 2017-05-10 中南大学湘雅医院 Method for segmenting vasa sanguinea retinae image
CN107133959A (en) * 2017-06-12 2017-09-05 上海交通大学 A kind of quick vessel borders three-dimensional dividing method and system

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111227822A (en) * 2018-11-28 2020-06-05 苏州润心医疗器械有限公司 Coronary artery blood flow reserve fraction calculation method based on myocardial blood flow volume and CT image
CN111227821A (en) * 2018-11-28 2020-06-05 苏州润心医疗器械有限公司 Microcirculation resistance index calculation method based on myocardial blood flow and CT (computed tomography) images
CN111227822B (en) * 2018-11-28 2022-02-11 苏州润迈德医疗科技有限公司 Coronary artery blood flow reserve fraction calculation method based on myocardial blood flow volume and CT image
CN111227821B (en) * 2018-11-28 2022-02-11 苏州润迈德医疗科技有限公司 Microcirculation resistance index calculation method based on myocardial blood flow and CT (computed tomography) images
CN110120031A (en) * 2019-04-02 2019-08-13 四川锦江电子科技有限公司 A kind of method and apparatus obtaining vascular flow deposit score
CN110120031B (en) * 2019-04-02 2022-05-31 四川锦江电子科技有限公司 Method and device for obtaining blood flow reserve fraction of blood vessel
WO2021087967A1 (en) * 2019-11-04 2021-05-14 苏州润迈德医疗科技有限公司 Method and apparatus for acquiring blood vessel assessment parameter on basis of physiological parameter, and storage medium
CN111134651B (en) * 2019-12-09 2022-03-08 杭州脉流科技有限公司 Method, device and system for calculating fractional flow reserve based on intracavity images and computer storage medium
CN111134651A (en) * 2019-12-09 2020-05-12 杭州脉流科技有限公司 Method, device and system for calculating fractional flow reserve based on intracavity images and computer storage medium
CN111161342A (en) * 2019-12-09 2020-05-15 杭州脉流科技有限公司 Method, device, equipment and system for obtaining fractional flow reserve based on coronary angiography image and readable storage medium
CN111161342B (en) * 2019-12-09 2023-08-29 杭州脉流科技有限公司 Method, apparatus, device, system and readable storage medium for obtaining fractional flow reserve based on coronary angiography image
CN112690814A (en) * 2020-11-06 2021-04-23 杭州阿特瑞科技有限公司 Low-error coronary artery blood flow reserve fraction measuring method
CN112971818B (en) * 2021-01-28 2022-10-04 杭州脉流科技有限公司 Method and device for acquiring microcirculation resistance index, computer equipment and storage medium
CN112971818A (en) * 2021-01-28 2021-06-18 杭州脉流科技有限公司 Method and device for rapidly acquiring microcirculation resistance index, computer equipment and storage medium
CN113995388A (en) * 2021-12-13 2022-02-01 数坤(北京)网络科技股份有限公司 Fractional flow reserve calculation method and device, electronic equipment and readable storage medium
CN116109788A (en) * 2023-02-15 2023-05-12 张春阳 Method for modeling and reconstructing solid piece
CN116109788B (en) * 2023-02-15 2023-07-04 张春阳 Method for modeling and reconstructing solid piece
CN116128864A (en) * 2023-02-22 2023-05-16 北京医准智能科技有限公司 Fractional flow reserve evaluation method, fractional flow reserve evaluation device, electronic equipment and storage medium
CN116128864B (en) * 2023-02-22 2024-04-23 浙江医准智能科技有限公司 Fractional flow reserve evaluation method, fractional flow reserve evaluation device, electronic equipment and storage medium
CN116636826A (en) * 2023-07-27 2023-08-25 深圳市爱保护科技有限公司 Training method and device of blood pressure estimation model, electronic equipment and storage medium
CN116636826B (en) * 2023-07-27 2023-09-22 深圳市爱保护科技有限公司 Training method and device of blood pressure estimation model, electronic equipment and storage medium

Similar Documents

Publication Publication Date Title
CN108735270A (en) Blood flow reserve score acquisition methods, device, system and computer storage media based on dimensionality reduction model
US11583340B2 (en) Method and system for image processing to determine blood flow
US20220406470A1 (en) Systems and methods for processing electronic images to determine flow using flow ratio
AU2017200000B2 (en) Method and system for modeling blood flow with boundary conditions for optimized diagnostic performance
EP3140757B1 (en) Method and system for non-invasive functional assessment of coronary artery stenosis using flow computations in models based on diseased patients and hypothetical normal anatomical models
CN110853029A (en) Method, system, and medium for automatically predicting blood flow characteristics based on medical images
CN114664455A (en) Coronary artery blood flow reserve fraction calculation method and device
WO2022136688A1 (en) Non-invasive method for determining a vessel damage indicator

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination