CN109528176A - A kind of cerebrovascular characteristic information analysis system and method - Google Patents
A kind of cerebrovascular characteristic information analysis system and method Download PDFInfo
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention belongs to cerebrovascular characteristic information analysis technical fields, disclose a kind of cerebrovascular characteristic information analysis system and method, comprising: image capture module, blood pressure detecting module, main control module, blood flow measurement module, quantitative analysis module, index parameter drafting module, data memory module, display module.The boundary condition that the present invention takes personalized flow velocity and data on flows to emulate as cerebrovascular Fluid Mechanics Computation by blood flow measurement module avoids the deviation of simulation result caused by the boundary condition of use experience value or model pre-estimating；Meanwhile the cerebrovascular is split in initial data by quantitative analysis module, it identifies Wills loop section, more accurate result can be obtained；Original discrete skeleton is fitted using B-spline curves method, makes vascular skeleton form serialization, so as to obtain the characteristic quantity at any point on blood vessel, obtains more accurate characteristic quantity calculated result；An accurate data reference standard is provided for the diagnosis of disease for doctor.
Description
Technical field
The invention belongs to cerebrovascular characteristic information analysis technical field more particularly to a kind of cerebrovascular characteristic information analysis systems
System and method.
Background technique
The cerebrovascular, full name cerebrovascular disease.It is generally divided into hemorrhagic cerebrovascular disease (cerebral hemorrhage, subarachnoid hemorrhage) and lacks
Hemorrhagic cerebrovascular disease (cerebral embolism, transient ischemic attack, cerebral thrombosis) two major classes.Cerebral embolism, can be there are many disease institute
The embolus of generation enters blood, blocks cerebral vessels and induces.Clinically with heart disease for the most common reason；Followed by bone
Fat enters blood after folding or wound；Worm's ovum or bacterium infection；The air such as pneumothorax enter blood, the factors such as embolus that phlebitis is formed, embolism
Caused by the cerebrovascular.Transient ischemic attack, (abbreviation TIA is called cockleshell or transient ischemic attack), the cause of disease with
Cerebral arteriovenous malformation is related, is dysfunction caused by brain tissue transience, ischemic, focal lesion.Cerebral thrombosis, mostly by
The blood clotting that atherosclerosis, various arteritis, wound and other physical factors, blood disease cause cerebrovascular local patholoic change to be formed
Block is blocked and is fallen ill.However, existing cerebrovascular characteristic information analysis system cannot accurately measure the cerebrovascular blood flow in part
Mechanical Data；Meanwhile doctor is for the diagnosis of cranial vascular disease also simply by piece subjective judgement is seen at present, there is no one
Accurate data reference standard.
In conclusion problem of the existing technology is:
Existing cerebrovascular characteristic information analysis system cannot accurately measure the cerebrovascular haemodynamics data in part；Together
When, doctor is for the diagnosis of cranial vascular disease also simply by piece subjective judgement is seen at present, and there is no an accurate data
Reference standard.
In the prior art, medical picture pick-up device cannot effectively avoid medical picture pick-up device from being done by extraneous or oneself factor
It disturbs, easily causes the situation of the inaccuracy of cerebrovascular image data acquiring to occur, cerebrovascular image data can not accurately be obtained；It is existing
The high blood pressure detecting of accuracy cannot effectively be provided in technology as a result, making that the prohibited data detection of blood pressure is true, reliability is low by having,
Life support cannot be provided for patient, influence medical staff's working efficiency；In the prior art cannot to the cerebrovascular image of acquisition,
The data such as blood pressure carry out quantization storage processing, and storage efficiency is low, and working efficiency is low, cannot accomplish to carry out patient's cerebrovascular situation
It timely analyzes, delay treatment.
Summary of the invention
In view of the problems of the existing technology, the present invention provides a kind of cerebrovascular characteristic information analysis system and methods.
The invention is realized in this way a kind of cerebrovascular characteristic information analysis method, the cerebrovascular characteristic information analysis
Method the following steps are included:
Step 1, medical picture pick-up device are acquired patient's cerebrovascular image data using gray model；By using
Instrument for measuring blood pressure with principal component analysis is acquired the blood pressure data information of patient；
Step 2 obtains the color cloud picture of haemodynamics information according to the image of acquisition and haemodynamics feature is joined
Number；Processing, the characteristic quantity of every section of blood vessel of quantitative analysis are split by cerebrovascular data of the particle swarm optimization algorithm to acquisition；
Step 3 draws out cerebrovascular indices curve graph by data processing software；
Step 4 carries out quantization storage using cerebrovascular image, blood pressure data of the memory to acquisition and handles；Pass through display
Device shows patient's cerebrovascular image, blood pressure, flow characteristic parameter.
Further, the medical picture pick-up device in the step 1 carries out patient's cerebrovascular image data using gray model
Acquisition, gray model are as follows: GM (1,1) model is equipped with variable X(0)Original data sequence:
X(0)={ x(0)(1),x (0)(2) ...,x (0)(n)}
N is original cerebrovascular image data number；The corresponding time is ti(n=1,2 ..., n).
Further, quantization storage is carried out using cerebrovascular image, blood pressure data of the memory to acquisition in the step 4
Processing, uses with drag:
x(t)=p(t)eJp (t)=p(t)exp[j2πf0t]；
In formula, f0=fs+fd, fd are Doppler frequency.
Another object of the present invention is to provide a kind of cerebrovascular for realizing the cerebrovascular characteristic information analysis method is special
Information analysis system is levied, the cerebrovascular characteristic information analysis system includes:
Image capture module is connect with main control module, for acquiring patient's cerebrovascular picture number by medical picture pick-up device
According to；
Blood pressure detecting module, connect with main control module, for acquiring patient blood pressure data's information by instrument for measuring blood pressure；
Main control module is joined with image capture module, blood pressure detecting module, blood flow measurement module, quantitative analysis module, index
Number drafting module, data memory module, display module connection, work normally for controlling modules by single-chip microcontroller；
Blood flow measurement module, connect with main control module, for obtaining the coloured silk of haemodynamics information according to the image of acquisition
Color cloud atlas and haemodynamics characteristic parameter；
Quantitative analysis module, connect with main control module, for the cerebrovascular data by particle swarm optimization algorithm to acquisition
It is split processing, the characteristic quantity of every section of blood vessel of quantitative analysis；
Index parameter drafting module, connect with main control module, for drawing out cerebrovascular items by data processing software
Index curve graph；
Data memory module is connect with main control module, for cerebrovascular image, the blood pressure etc. by memory storage acquisition
Data；
Display module is connect with main control module, for showing that patient's cerebrovascular image, blood pressure, blood flow are special by display
Levy parameter.
Another object of the present invention is to provide a kind of computers using the cerebrovascular characteristic information analysis method.
Advantages of the present invention and good effect are as follows:
The present invention takes personalized flow velocity and data on flows as cerebrovascular Fluid Mechanics Computation by blood flow measurement module
The boundary condition of emulation avoids the deviation of simulation result caused by the boundary condition of use experience value or model pre-estimating；This
Invention is based entirely on iconography means, it may not be necessary to contrast agent is injected, it is convenient, noninvasive；Meanwhile being existed by quantitative analysis module
The cerebrovascular is split in initial data, identifies Wills loop section, Wills ring bone is carried out using skeleton line extraction algorithm
Stringing extracts, and obtains Wills ring skeleton line and its sampled point radius geometrical model.Every section of blood vessel on skeleton line is carried out semantic
Mark and rule sampling, and calculate the characteristic quantity at sampled point；It can obtain more accurate result；Using B-spline curves side
Method is fitted original discrete skeleton, obtains vascular skeleton form serialization so as to obtain the characteristic quantity at any point on blood vessel
To more accurate characteristic quantity calculated result；An accurate data reference standard is provided for the diagnosis of disease for doctor.
Medical picture pick-up device of the invention is acquired patient's cerebrovascular image data using gray model, effectively avoids
Medical picture pick-up device is influenced to cause the situation of the inaccuracy of cerebrovascular image data acquiring by extraneous or oneself factor, effectively
Improve the accuracy of cerebrovascular image data acquiring；The present invention uses the instrument for measuring blood pressure with Principal Component Analysis Algorithm to patient
Blood pressure data information be acquired, the accuracy of blood pressure detecting can be effectively provided so that the detection data of blood pressure it is accurate, can
It leans on, provides life support for patient, improve the convenience in work for medical staff；The present invention is utilized with quantification treatment model
Memory carries out quantization storage processing to data such as the cerebrovascular image of acquisition, blood pressures, effectively improves storage efficiency, guarantees work
Quality provides working efficiency.
Detailed description of the invention
Fig. 1 is cerebrovascular characteristic information analysis method flow diagram provided in an embodiment of the present invention.
Fig. 2 is cerebrovascular characteristic information analysis system structure diagram provided in an embodiment of the present invention；
In figure: 1, image capture module；2, blood pressure detecting module；3, main control module；4, blood flow measurement module；5, quantitative point
Analyse module；6, index parameter drafting module；7, data memory module；8, display module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, cerebrovascular characteristic information analysis method provided in an embodiment of the present invention specifically includes the following steps:
S101: medical picture pick-up device is acquired patient's cerebrovascular image data using gray model；By using tool
There is the instrument for measuring blood pressure of principal component analysis to be acquired the blood pressure data information of patient；
S102: the color cloud picture and haemodynamics characteristic parameter of haemodynamics information are obtained according to the image of acquisition；
Processing, the characteristic quantity of every section of blood vessel of quantitative analysis are split by cerebrovascular data of the particle swarm optimization algorithm to acquisition；
S103: cerebrovascular indices curve graph is drawn out by data processing software；
S104: quantization storage is carried out to data such as the cerebrovascular image of acquisition, blood pressures using memory and is handled；Pass through display
Device shows patient's cerebrovascular image, blood pressure, flow characteristic parameter.
In step S101, medical treatment picture pick-up device provided in an embodiment of the present invention is using gray model to patient's cerebrovascular image
Data are acquired, and medical picture pick-up device is effectively avoided to be caused cerebrovascular image data to adopt by extraneous or oneself factor influence
The situation of the inaccuracy of collection, effectively improves the accuracy of cerebrovascular image data acquiring；The gray model specifically used are as follows:
G M (1,1) model is equipped with variable X(0)Original data sequence:
X(0)={ x(0)(1), x(0)(2) ..., x(0)(n)}
N is original cerebrovascular image data number；The corresponding time is ti(n=1,2 ..., n)；
Single order accumulator module X is generated with A G O (Accumullated Generating Operation)(1)
X(1)={ x(1)(1), x(1)(2) ..., x(1)(n)}
By single order Grey Simulation X(1)The differential equation of composition are as follows:
According to derivative discrete form, the differential equation can be write as in the matrix form:
Y=AU
Wherein,
Using the principle of least square, estimates of parameters can be acquired are as follows:
Returning to the original differential equation has:
It must solve are as follows:
Discrete form are as follows:
Wherein, k is the cerebrovascular image data number for participating in detection；
General type are as follows:
Wherein, P > 1 is test point；Original cerebrovascular image data sequence after then detecting are as follows:
Alternatively, expressing with can simplify are as follows:
Entire gray model detection process can be expressed as:
Wherein, IAGO, AGO are respectively inverse accumulated generating sequence and Accumulating generation sequence.
It is provided in an embodiment of the present invention to use the instrument for measuring blood pressure with Principal Component Analysis Algorithm to patient in step S101
Blood pressure data information be acquired, the accuracy of blood pressure detecting can be effectively provided so that the detection data of blood pressure it is accurate, can
It leans on, provides life support for patient, improve the convenience in work for medical staff；Characteristic target is obtained using Principal Component Analysis
Principal component, meanwhile, utilize X2Method of inspection carries out just too distribution inspection to principal component；
N (μ, σ can be just distributed very much2), μ, σ2It is unknown, point estimation is carried out to it using maximal possibility estimation, is obtained:
It must be distributed probability density, using X2The normal distribution of method of inspection test samples, formula are as follows:
Wherein N is sample number, and l is packet count, riFor actual frequency, tiFor theoretical frequency.
In step S104, it is provided in an embodiment of the present invention using memory to data such as the cerebrovascular image of acquisition, blood pressures
Quantization storage processing is carried out, storage efficiency is effectively improved, guarantees work quality, working efficiency is provided；
Memory carries out quantization storage processing to data such as the cerebrovascular image of acquisition, blood pressures, specifically uses with drag:
x(t)=p(t)ejp(t)=p(t)exp[j2πf0t]；
In formula, f0=fs+fd, fd are Doppler frequency；
The data-signals x such as the cerebrovascular image of storage, blood pressure(t)Apply phase quantization processing, in k-th of channel, increases phase
Position delayThereafter pass through an ideal amplitude limiter, be described using following mathematical expression,
In formula:For the data quantizations phase such as cerebrovascular image, blood pressure, N=2MFor data such as cerebrovascular image, blood pressures
Quantification gradation, M are the quantization digit of the data such as cerebrovascular image, blood pressure；
Quantization system is made of N number of autonomous channel, number k, k=0~N-1.
The output of limiter and a sequence of complex numbersIt is multiplied, then, all channels, which are added, to be quantified
The signal of the data such as cerebrovascular image, blood pressure.
As shown in Fig. 2, cerebrovascular characteristic information analysis system provided by the invention includes:
Image capture module 1, main control module 3, blood flow measurement module 4, quantitative analysis module 5, refers to blood pressure detecting module 2
Mark parameter drafting module 6, data memory module 7, display module 8.
Image capture module 1 is connect with main control module 3, for acquiring patient's cerebrovascular image by medical picture pick-up device
Data；
Blood pressure detecting module 2 is connect with main control module 3, for acquiring patient blood pressure data's information by instrument for measuring blood pressure；
Main control module 3, with image capture module 1, blood pressure detecting module 2, blood flow measurement module 4, quantitative analysis module 5,
Index parameter drafting module 6, data memory module 7, display module 8 connect, normal for controlling modules by single-chip microcontroller
Work；
Blood flow measurement module 4 is connect with main control module 3, for obtaining haemodynamics information according to the image of acquisition
Color cloud picture and haemodynamics characteristic parameter；
Quantitative analysis module 5 is connect with main control module 3, for the cerebrovascular number by particle swarm optimization algorithm to acquisition
It is handled according to being split, the characteristic quantity of every section of blood vessel of quantitative analysis；
Index parameter drafting module 6 is connect with main control module 3, each for drawing out the cerebrovascular by data processing software
Item index curve graph；
Data memory module 7 is connect with main control module 3, for cerebrovascular image, the blood pressure by memory storage acquisition
Etc. data；
Display module 8 is connect with main control module 3, for showing patient's cerebrovascular image, blood pressure, blood flow by display
Characteristic parameter.
4 measurement method of blood flow measurement module provided by the invention is as follows:
1) the cerebrovascular computed tomography images of acquisition human body and the image for calculation of boundary conditions；
2) reconstruction processing is carried out to the scan image, obtains cerebrovascular three-dimensional geometrical structure by rebuilding, and handle phase
Position enhancing data, extract boundary information needed for emulating；
3) pre-treatment, including smoothing processing, grid dividing and boundary condition are carried out to the cerebrovascular three-dimensional geometrical structure
Setting；
4) fluid emulation method for solving is arranged in building model, solves cerebrovascular three-dimensional geometrical structure hemodynamic everywhere
Learn information；
5) simulation result and measurement result are compared, adjustment simulation mathematical model and solution parameter export haemodynamics
The color cloud picture and haemodynamics characteristic parameter of information.
Specific as follows in step 4) provided by the invention: the model includes entrance model, outlet model, vascular wall model
And Blood Model；Wherein, entrance model is used to be arranged the entrance boundary condition of fluid mechanical emulation, and outlet model is for being arranged stream
The export boundary condition of mechanics emulation, vascular wall model are used to be arranged the boundary condition of vascular wall, and Blood Model is for being arranged
Meet the haemodynamics model of blood flow feature；It is set in each parameter to entrance, outlet, vascular wall and flow model
It postpones, then method for solving and the condition of convergence is configured, by solving partial differential equation, to the blood flow in each grid
Mechanical information is solved, thus to obtain haemodynamics information everywhere.
5 analysis method of quantitative analysis module provided by the invention is as follows:
Step 1, according to collected cerebrovascular DICOM data, the maximum intensity projection figure of the data is obtained, using grain
Subgroup optimization algorithm is split processing to initial data, obtains segmentation volume data and Mesh data；
Step 2, manual identified goes out Wills loop section from the data after dividing processing, and uses skeleton line extraction algorithm
Wills ring skeleton line drawing is carried out, Wills ring skeleton line and its sampled point vessel radius geometrical model are obtained；
Step 3, semantic mark is carried out to the vessel branch on Wills ring skeleton line referring to maximum intensity projection figure, and set
Fixed sampling rule；
Step 4, it carries out curve fitting to every section of blood vessel on Wills ring skeleton line, utilizes obtained continuous Wills ring
Skeleton line curve calculates the characteristic quantity of every section of blood vessel；
Step 5, data statistic analysis is carried out to calculated result.
The sampling rule set in step 3 provided by the invention are as follows: carry out uniform sampling by length on single hop blood vessel.
Step 4 provided by the invention is fitted every section of blood vessel on Wills ring skeleton line using B-spline fitting process.
The method that step 4 provided by the invention calculates the characteristic quantity of blood vessel is as follows:
Step 4.1, the local feature amount at sampled point is calculated；
Step 4.1.1 calculates radius, the method is as follows:
Original discrete point skeleton is fitted using ball B-spline；
The one section of blood vessel to be calculated is sampled according to the sampling rule of setting；
The enveloping surface that the boundary of angiosomes is regarded as to one-parameter sphere solves the half of blood vessel according to analytic geometry knowledge
Diameter；
Step 4.1.2, computational length, curvature, torsion, sampled point and head and the tail put the angle value of line, the method is as follows:
It is carried out curve fitting using B-spline curves fitting process；
The one section of blood vessel to be calculated is sampled according to the sampling rule of setting；
The angle value that length, curvature, torsion, sampled point and head and the tail put line is solved according to analytic geometry knowledge.
Step 4.2, global characteristics amount is calculated；
Curvature and torsion are calculated separately to the integral of arc length, every section of blood vessel is calculated according to the volume data that step 1 is partitioned into
Volume, the Mesh data being partitioned into according to step 1 calculate the surface area of every section of blood vessel.
When the invention works, firstly, acquiring patient's cerebrovascular image using medical picture pick-up device by image capture module 1
Data；Patient blood pressure data's information is acquired using instrument for measuring blood pressure by blood pressure detecting module 2；Secondly, main control module 3 passes through blood
Flow measurement module 4 obtains the color cloud picture and haemodynamics characteristic parameter of haemodynamics information according to the image of acquisition；It is logical
It crosses quantitative analysis module 5 and is split processing, every section of quantitative analysis using cerebrovascular data of the particle swarm optimization algorithm to acquisition
The characteristic quantity of blood vessel；Cerebrovascular indices curve graph is drawn out using data processing software by index parameter drafting module 6；
Then, the data such as cerebrovascular image, the blood pressure acquired by data memory module 7 using memory storage；Finally, passing through display
Module 8 shows patient's cerebrovascular image, blood pressure, flow characteristic parameter using display.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. a kind of cerebrovascular characteristic information analysis method, which is characterized in that the cerebrovascular characteristic information analysis method include with
Lower step:
Step 1, medical picture pick-up device are acquired patient's cerebrovascular image data using gray model；By using having
The instrument for measuring blood pressure of principal component analysis is acquired the blood pressure data information of patient；
Step 2 obtains the color cloud picture and haemodynamics characteristic parameter of haemodynamics information according to the image of acquisition；It is logical
It crosses particle swarm optimization algorithm and processing, the characteristic quantity of every section of blood vessel of quantitative analysis is split to the cerebrovascular data of acquisition；
Step 3 draws out cerebrovascular indices curve graph by data processing software；
Step 4 carries out quantization storage using cerebrovascular image, blood pressure data of the memory to acquisition and handles；It is aobvious by display
Show patient's cerebrovascular image, blood pressure, flow characteristic parameter.
2. cerebrovascular characteristic information analysis method as described in claim 1, which is characterized in that the medical treatment in the step 1 is taken the photograph
As equipment utilization gray model is acquired patient's cerebrovascular image data, gray model are as follows: G M (1,1) model is equipped with and becomes
Measure X(0)Original data sequence:
X(0)={ x(0)(1), x(0)(2) ..., x(0)(n)}
N is original cerebrovascular image data number；The corresponding time is ti(n=1,2 ..., n).
3. cerebrovascular characteristic information analysis method as described in claim 1, which is characterized in that utilize storage in the step 4
Device carries out quantization storage processing to cerebrovascular image, the blood pressure data of acquisition, uses with drag:
x(t)=p(t)ejp(t)=p(t)exp[j2πf0t]；
In formula, f0=fs+fd, fd are Doppler frequency.
4. a kind of cerebrovascular characteristic information analysis system for realizing cerebrovascular characteristic information analysis method described in claim 1,
It is characterized in that, the cerebrovascular characteristic information analysis system includes:
Image capture module is connect with main control module, for acquiring patient's cerebrovascular image data by medical picture pick-up device；
Blood pressure detecting module, connect with main control module, for acquiring patient blood pressure data's information by instrument for measuring blood pressure；
Main control module is drawn with image capture module, blood pressure detecting module, blood flow measurement module, quantitative analysis module, index parameter
Molding block, data memory module, display module connection, work normally for controlling modules by single-chip microcontroller；
Blood flow measurement module, connect with main control module, for obtaining the colored cloud of haemodynamics information according to the image of acquisition
Figure and haemodynamics characteristic parameter；
Quantitative analysis module, connect with main control module, for being carried out by cerebrovascular data of the particle swarm optimization algorithm to acquisition
Dividing processing, the characteristic quantity of every section of blood vessel of quantitative analysis；
Index parameter drafting module, connect with main control module, for drawing out cerebrovascular indices by data processing software
Curve graph；
Data memory module is connect with main control module, is counted for cerebrovascular image, the blood pressure etc. by memory storage acquisition
According to；
Display module is connect with main control module, for showing that patient's cerebrovascular image, blood pressure, flow characteristic are joined by display
Number.
5. a kind of computer using cerebrovascular characteristic information analysis method described in claims 1 to 3 any one.
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| CN112826457A (en) * | 2020-12-31 | 2021-05-25 | 苏州爱琴生物医疗电子有限公司 | Brain-based sign information detection device and method and related equipment |
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