CN110415243A - A kind of angiogram data processing method and image data processing system - Google Patents
A kind of angiogram data processing method and image data processing system Download PDFInfo
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Abstract
The invention discloses a kind of angiogram data processing method and image data processing systems.Based on handling angiographic sequence image data, from treated, image data calculates vascular flow differential parameter, utilize principle of hemodynamics and Differential Principle, the differential analysis of process is entirely filled in heart to blood flow parameter, it calculates and obtains the differential score that blood flow entirely fills process, it can be used in assessing whether blood flow is entirely occurring blocking and retarding degree during the filling process, to be able to the stenosis of assessment blood vessel.
Description
Technical field
The present invention relates to technical field of medical image processing, in particular to a kind of angiogram data processing method and
Image data processing system.
Background technique
Cardiovascular disease is all one of the significant damage of human health all the time, and wherein cardiovascular is narrow can be to cardiac muscle
Blood supply causes to directly affect, the serious disease that will lead to myocardial infarction etc. and endanger patient vitals, in clinical application to blood vessel
The assessment of stenosis, which just seems, to be even more important, and angiography can really reflect the narrow positions of blood vessel, but cannot accurately comment
Estimate the stenosis of blood vessel under complex situations.
Blood flow differential score (Fractional Flow Differential Coefficient, FFD) refers to that blood vessel is supplied
Myocardial region is in blood flow the ratio between the blood flow variable quantity at each moment and maximum blood flow variable quantity during the filling process, blood flow differential score
It can objectively reflect blood flow in the blood flow variation degree at each moment of entire full process, when blood flow variable quantity is entirely filling
Present during being full of when stablizing, represent intravascular blood flow be it is unobstructed smoothly, when blood flow variable quantity occurs within a certain section of moment
Increase after being substantially reduced, represents this section of blood vessel there may be narrow situation, blood flow receives resistance when through this section of narrow positions
Hinder, blood flow differential score is the method effectively assessed hemadostewnosis degree, has weight to the therapeutic strategy of coronary artery stenosis
The directive significance wanted.
It is to obtain blood vessel by intervening the pressure sensor of blood vessel that the stenosis of assessment blood vessel, which mainly uses method, at present
The blood flow reserve score of blood vessel, such as interposing catheter or seal wire are determined in normal portions and the pressure difference ratio of narrow positions,
The risk of the invasive blood trouble pipe of the acquisition methods of this kind of blood flow reserve score, no forecasting mechanism are clinical costly；Another is commented
Method is estimated by analyzing angiographic sequence image, calculates blood flow in the pressure difference of normal portions and narrow positions, from
And blood flow reserve score is obtained, this method can obtain blood flow reserve score under normal circumstances, but to complicated tortuous multistage
The acquisition of branching blood vessels blood flow reserve score just lacks accuracy.
Summary of the invention
It is an object of the invention to overcome the method using intervention blood vessel in the presence of the prior art to obtain blood flow reserve
The risk of the invasive blood trouble pipe of score, without forecasting mechanism, clinical costly, using angiographic sequence image analysis pressure difference
Method can not accurately obtain the above-mentioned deficiency of complicated tortuous multistage branching blood vessels blood flow reserve score, provide a kind of blood vessel and make
Shadow image processing method, image data processing system, image display method, storage medium and equipment.
In order to achieve the above-mentioned object of the invention, the present invention provides following technical schemes:
A kind of angiogram data processing method,
The angiographic sequence image data in predetermined amount of time is extracted, the sequential image data includes several frames, institute
Stating predetermined amount of time includes at least one angioplerosis period；
According to the time interval of amount of pixel change and the frame in the sequence image, the institute of angioplerosis process is calculated
State the blood flow that frame corresponds to the moment；
Calculate the blood flow differential score of the blood flow relative time at the corresponding moment.
Preferably, de-noising and image enhancement are carried out to the sequential image data.
Preferably, the processing method,
Include the steps that the image real time transfer of angiography being the sequential image data；
Include the steps that carrying out the sequence image de-noising, image enhancement, image recognition, described image identification is by institute
The blood vessel for stating every frame image in sequence image is distinguished from background；
Including passing through the new sequence image of the full process of blood flow in frame image every in sequence image formation blood vessel
Step；
Including calculating the time interval in the new sequence image between every frame image, according to the new sequence image
In specify some described cross section, calculate the cross section in the amount of pixel change of several consecutive frame blood-vessel images, pass through institute
State amount of pixel change and the step of the time interval calculates the blood flow of the cross section；
The blood flow including entirely filling each moment of process by blood vessel calculates the blood flow at blood vessel each moment
The step of differential score.
It is further preferred that the processing method, comprising the following steps:
A, angiography obtains a series of described image data of blood vessel, it is converted to the first sequence according to unified format
Column image IK, M × N, wherein K indicates that image sequence frame number, M indicate every frame image horizontal pixel number, and N indicates that every frame image is longitudinal
Number of pixels；
B, blood vessel is determined proximally and distally in the area-of-interest of image, according to the form and situation of change of blood vessel,
Blood vessel proximal end is determined as normal blood flow by place, blood vessel distal end is determined as hemadostewnosis position；
C, using Laplace transform (Laplace Transform) and/or using based on partial differential equation (Partial
Differential Equation, PDE) non-linear filtering method to the IK, M × NCarry out denoising；
D, it is handled and/or using self-adapting histogram equilibrium method using edge sharpening to the IK, M × NCarry out image increasing
Strength reason, improves the identification of blood vessel；
E, using Scale invariant features transform (Scale Invariant Feature Transform, SIFT) to described
IK, M × NCarry out the transformation and reduction of several scales；
F, to I described after reductionK, M × NIn every frame image carry out image gray processing, image enhancement, image recognition processing,
Form the second sequence image V that blood flow in blood vessel fills processK, M × N, wherein K indicates that image sequence frame number, M indicate every frame image
Horizontal pixel number, N indicate every frame image longitudinal direction number of pixels；
G, the time of picture frame where contrast agent picture frame where the blood vessel proximal end reaches the blood vessel distal end is calculated
Interval and frame number by time interval and sequence image frame number can calculate the time interval T between every frame imageK；
H, in the VK, M × NIn specify some described cross section, calculate the cross section in several consecutive frame vessel graphs
The amount of pixel change of picture passes through the amount of pixel change and the TKThe cross section is calculated in the blood flow of the period；
I, the blood flow differential for calculating each moment entirely fills the blood flowmeter at each moment of process by blood vessel
The blood flow micro component for calculating each moment calculates the blood flow micro component at each moment and the ratio of the maximum blood flow micro component
Value, that is, calculate the blood flow differential score at each moment, obtains the blood vessel entirely change procedure of the blood flow during the filling process.
It is further preferred that the edge sharpening processing uses gamma correction (Gamma Correction).
It is further preferred that after executing the step B, first to the IK, M × NGray processing processing is carried out, then executes the step
Rapid C.
It is further preferred that the step E the following steps are included:
E1, to the IK, M × NConvolution algorithm is carried out with Gaussian kernel, the difference of variance is selected according to Gaussian kernel, is constituted different
The image of scale parameter；
E2, to the IK, M × NIn every frame image carry out several hierarchical transformations, in each hierarchical transformation, from original figure
Pixel is extracted at interval as in, forms new image, the first transform sequence image is generated after final hierarchical transformation；
E3, several level reduction, each hierarchical transformation are carried out to every frame image in the first transform sequence image
In, pixel is sequentially extracted from original image, interval forms new image, to pixel not set in new image by it
Neighbor pixel carries out linear interpolation and obtains, and generates the second transform sequence image after final level reduction.
It is further preferred that the linear interpolation using bilinear interpolation method (Bilinear Interpolation) into
Row image restoring.
The present invention also provides a kind of image data processing systems, comprising:
Image receiver module is sequence for receiving a series of images data of blood vessel, and by described image data processing
Image；
Image processing module is formed in blood vessel for carrying out de-noising, image enhancement, image recognition to the sequence image
Blood flow fills the new sequence image of process, according to the time interval and certain specified between frame image every in new sequence image
The blood flow of the cross section is calculated in the amount of pixel change of several consecutive frame blood-vessel images in a vessel cross-sections, according to
The blood flow calculates the blood flow differential score at blood vessel each moment；
Human-machine interface module, for showing the sequence image and the blood flow differential score.
Preferably, which further includes image storage module, and described image memory module is for storing described image
Data, the sequence image, the new sequence image and the blood flow differential score.
Preferably, which further includes digital subtraction angiography machine, and the digital subtraction angiography machine is used for
Angiography obtains a series of images data of blood vessel, and is supplied to described image receiving module.
It is further preferred that described image receiving module includes image transmitting interface, for the received cable of image, image
Receiving interface and image converter, described image coffret is for connecting the digital subtraction angiography machine, described image
Converter is the processing of the described image data of transmitting the digital subtraction angiography machine according to specified Data Format Transform
Unit.
It is further preferred that described image converter is image pick-up card.
It is further preferred that described image memory module includes control logic, physical storage medium, such as image storage is soft
Part, memory, hard disk.
It is further preferred that the human-machine interface module includes display, printer, user interface, mouse and keyboard.
It is further preferred that described image processing module includes control logic, image processing logic, physical processing unit,
Such as picture processing chip, image processing software.
The present invention also provides a kind of image display method, the institute obtained according to the processing method as described in any of the above item
Blood flow differential score is stated, indicates the corresponding blood flow differential score with from the transition color of red, orange, yellow, green, blue, blue, purple
Range, the blood flow differential score is more than or equal to 0.00, and is less than or equal to 1.00, and it is micro- to represent the blood flow with red
Divide score to be lower than 0.70 degree, represents the blood flow differential score close to 1.00 degree with purple.
Preferably, the color is shown on blood-vessel image or is shown in the blood flow differential score numerically.
The present invention also provides a kind of computer readable storage mediums, are stored thereon with computer program, which is located
Manage the processing method or realization display methods as described above realized as described in any of the above item when device executes.
The present invention also provides a kind of electronic equipment, comprising:
Memory is stored thereon with computer program；
Processor, for executing the described program in the memory, to realize the processing side as described in any of the above item
Method realizes display methods as described above.
In conclusion by adopting the above-described technical solution, the beneficial effects of the present invention are:
The present invention is based on handling angiographic sequence image data, from treated, image data calculates blood vessel blood
Differential parameter is flowed, using principle of hemodynamics and Differential Principle, entirely fills the differential point of process in heart to blood flow parameter
Analysis calculates and obtains the differential score that blood flow entirely fills process, can obtain corresponding blood flow reserve score；Due to using timing
Differentiated manner corresponding with image frame sequence, the process that can be changed with time by pixel in sequence image reflect blood flow on the whole
Interrupted degree, moreover it is possible to reflect the interrupted degree of certain section of blood flow from part, or even can analyze and obtain complicated song
Blood flow reserve score at the multistage blood vessel of folding is avoided using the intervention possible wound risk of blood vessel mode and can not be pre-
The defect of survey avoids the defect that process assessment can not be carried out using other blood-vessel image analysis methods；Using meeting contrast agent
Decomposed with blood flow Nonlinear Diffusion characteristic based on partial differential equation, self-adapting histogram equilibrium, scale invariant feature and
The image processing method of reduction can more effectively eliminate noise compared with other methods, and blood-vessel image is enhanced, readily discernible, adopt
With high operation efficiency image processing method, storage and computing device, acquisition blood flow differential in the course of surgery can be rapidly realized
The assessment of score, overcome conventional method time-consuming, is costly, unpredictable, can not local evaluation the problems such as.
Specific embodiment
Below with reference to test example and specific embodiment, the present invention is described in further detail.But this should not be understood
It is all that this is belonged to based on the technology that the content of present invention is realized for the scope of the above subject matter of the present invention is limited to the following embodiments
The range of invention.
Embodiment 1
A kind of angiogram data processing method of the invention, comprising the following steps:
Step 1: angiography, obtains a series of image datas of blood vessel；
Step 2: a series of contrastographic pictures are converted to First ray image I according to unified formatK, M × N, wherein K is indicated
Image sequence frame number, M indicate every frame image horizontal pixel number, and N indicates every frame image longitudinal direction number of pixels；
Sequence image is a series of contrastographic pictures of the contrast agent from the proximal end of blood vessel to distal end, i.e. blood flow whithin a period of time
Entire full process in the blood vessels, the room and time relationship with Anatomical significance flowed in the blood vessels comprising blood；
Step 3: storage IK, M × N；
Step 4: display IK, M × N, blood vessel is determined proximally and distally in the area-of-interest of image, according to blood vessel
Blood vessel proximal end is determined as normal blood flow by place, blood vessel distal end is determined as hemadostewnosis position by form and situation of change；
Step 5: to IK, M × NCarry out gray processing processing；
If image is RGB color image, to IK, M × NGray processing processing is carried out, to reduce the amount of storage of image procossing, improve
Image procossing speed, calculation formula are as follows:
I (i, j)=0.299 × I (i, j, r)+0.758 × I (i, j, g)+0.114 × I (i, j, b)
Wherein, r, g, b are the RGB encoded radio of image slices vegetarian refreshments；
If image itself is gray level image, after executing step 4, step 5 is skipped, executes subsequent step；
Step 6: to IK, M × NCarry out denoising；
Denoising is carried out using Laplace transform, chooses the Laplace operator of 3 ranks in the present embodiment:
By with Laplace operator to IK, M × NIt is filtered, eliminates the high-frequency noise in image, be conducive to improve subsequent
Enhancing processing to vessel boundary, its calculation formula is:
Wherein G is the gray scale value matrix of the neighbor pixel composition centered on currently processed pixel, Iin(i, j) and
Iout(i, j) is the currently processed pixel before calculating and after calculating respectively；
According to IK, M × NComprising the Nonlinear Diffusion characteristic that contrast agent flows in the blood vessel, that is, presents and become with room and time
Change from high concentration to low concentration flow, using the non-linear filtering method based on partial differential equation to image further denoising at
Reason:
Wherein,For the gradient of image slices vegetarian refreshments, div is diffusion operator, fdiffuseIt (x) is spread function, intensity
Value range is 0.01~1.0 to coefficient A in the present embodiment, and value is 0.01~0.2, I to time step t in the present embodiment0
(i, j) is initialisation image；
Wherein, λ1、λ2It is the threshold value of image slices vegetarian refreshments gradient-norm with ω, value range is 0~10, is taken in the present embodiment
Value is 3,6 and 2, and coefficient B and C are constant, and value is 4 and 2 in the present embodiment, coefficientIn the present embodiment
Middle value is 0.2；
Using the Nonlinear diffusion filtering based on partial differential equation, I is iteratively calculatedK, M × N, iteration in the present embodiment
Number value range is 10~30 times；
As spread function fdiffuse(x) with image slices vegetarian refreshments gradient-normWhen reducing and being gradually increased, diffusion tends to
Smoothly；
When image slices vegetarian refreshments gradient-normIn [λ2- ω, λ2+ ω] between when, spread function fdiffuse(x) value
It is negative, that is, realizes and the sharpening enhancement of vessel boundary is handled；
When image slices vegetarian refreshments gradient-normWhen value is larger, spread function fdiffuse(x) value becomes small, thus compared with
Good artery-sparing edge；
Treated, and image not only effectively inhibits noise, but also has been effectively maintained the edge and minutia of blood vessel；
Step 7: to IK, M × NCarry out image enhancement processing；
Edge sharpening processing is carried out to the image of the blood vessel of complex shape and lesion situation, so that because form has subtle bifurcated
Vessel trunk it is apparent, identification is higher, avoids the calculating error introduced by the subtle bifurcated of blood vessel；
Edge sharpening uses gamma correction in the present embodiment, other similar algorithms of effect can also be used, and allows blood-vessel image
It is apparent with the edge of background image, support is provided for subsequent enhancing processing, its calculation formula is:
G=max [0, min [255, I (i, j)]] 1≤i≤M, 1≤j≤N
I (i, j)=Gamma [g]
Wherein Gamma is set of transform coefficients, and power exponent r sets value range as 0.1~10.0, g according to picture quality
For the gray value of image slices vegetarian refreshments；
To image edge acuity processing, the enhanced I of vessel boundary is obtainedK, M × N；
Because angiographic image background usually with the contrast of blood-vessel image it is lower, cause it is subsequent to blood-vessel image into
When row segmentation, be easy to cause and accidentally divide or the case where over-segmentation, and angiographic image include low frequency blood vessel signal and
The interference signal of high frequency；
Using self-adapting histogram equilibrium method to IK, M × NFurther implement enhancing processing, so that blood-vessel image and background
Image has more obvious difference, improves the identification of blood-vessel image, the calculating of the adaptive windows of self-adapting histogram equilibrium
Formula are as follows:
Im×n(k, l)=Hvalue[Im×n(k, l)]
Wherein, HvalueFor the adaptive windows measured value of image, m and n are respectively the pixel height and width degree of adaptive windows, at this
Value is 32 in embodiment, and iteration executes above-mentioned adaptive windows operation to pixel each in image, by IK, M × NIt carries out adaptive
Histogram equalization is answered to handle, so that interested angiosomes are able to have stronger contrast and identification with background area；
Step 8: blood-vessel image clearly, is accurately identified from background image；
Because heart has the characteristics that cycle movement, the position of blood-vessel image is also presented dynamic change movement, needs blood
Pipe image is clear from the background image of dynamic change, accurately identifies, moreover it is possible to keep the local feature of blood-vessel image；
The transformation and reduction for being carried out several scales to blood-vessel image using Scale invariant features transform, can effectively be identified
Blood-vessel image keeps the configuration of blood vessel, and can effectively keep the local feature of blood vessel；
To IK, M × NConvolution algorithm is carried out with Gaussian kernel, not only eliminates noise, but also smoothed image, variance is selected according to Gaussian kernel
Difference, constitute the image of different scale parameter, formula is as follows:
I (i, j, σ)=Fgauss(i, σ) * I (i, j)
Convolution is carried out to image using 3,5,7 rank Gaussian matrixes in the present embodiment, so that the image of 3 scales is constituted,
Such as:
Wherein G is the gray scale value matrix of the neighbor pixel composition centered on currently processed pixel；
Image is transformed to several level images, different according to the level of transformation, picture is extracted at interval from original image
Vegetarian refreshments forms new image, i.e., implements hierarchical transformation to blood-vessel image, thin in image after carrying out hierarchical transformation to image
Section interference can be suppressed, and the form and feature of image medium vessels can be enhanced；
To IK, M × NIn every frame image carry out several hierarchical transformations, generate the first new transform sequence image；
In the present embodiment, it extracts and is divided into 1 between pixel, the number of pixels of new image is original image after transformation
1/4, image can be transformed to 3~4 level images, blood-vessel image can be slackened or even be disappeared instead by excessive scale space transformation
It removes, causes excessively to convert and misidentify；
Several level image restorings are merged, it is different according to the level of transformation, pixel is sequentially extracted from original image
Point, interval form new image, carry out linear interpolation by its neighbor pixel to pixel not set in new image and obtain,
Level reduction is implemented to blood-vessel image；
Image restoring is carried out using bilinear interpolation method in the present embodiment, other interpolation methods can also be used；
Image after the reduction of several different levels is merged, new image is obtained, can effectively identify vessel graph
Picture keeps the configuration of blood vessel, and can effectively keep the local feature of blood vessel；
Several level reduction are carried out to every frame image in the first transform sequence image, generate the second new transform sequence
Image；
In the present embodiment, it is divided into 1 between interpolating pixel point, the number of pixels of new image is original image after reduction
4 times, image can be transformed to 3~4 level images；
Step 9: carrying out image enhancement, the step 8 of above-mentioned steps seven to every frame image in the second transform sequence image
Image recognition processing form the full process of blood flow in blood vessel (due to radiography until all images all handle completions in sequence
Process is exactly contrast agent in angioplerosis process, and sequence image is also to obtain in this process, therefore sequence image itself
Just comprising angioplerosis process) the second sequence image VK, M × N, wherein K indicates that image sequence frame number, M indicate that every frame image is horizontal
To number of pixels, N indicates every frame image longitudinal direction number of pixels；
Step 10: calculating the time interval of picture frame where contrast agent picture frame where blood vessel proximal end reaches blood vessel distal end
And frame number can calculate the time interval T between every frame image by time interval and sequence image frame numberK；
The digital subtraction angiography machine of different model has different contrastographic picture frame per second, therefore the time interval calculated
TKAlso can be different, in general, the frame per second of angiogram sequence image is 15~30 frames/second；
Step 11: calculating the blood flow that blood vessel entirely fills each moment of process by blood-vessel image and time interval
Amount；
In blood-vessel image VK, M × NSome specified cross-section calculates the amount of pixel change of several consecutive frame blood-vessel images,
Its formula is as follows:
Wherein, S is the lumen cross-sectional area of blood vessel, t0And tnThe start frame of respectively specified several blood-vessel image frames with
Abort frame, the amount of pixel change P [t] of blood vessel are the flow of Intravascular contrast agents, can be approximately that intravascular specified some is transversal
The blood flow F [t] in the time interval in face；
Step 12: calculating the blood flow differential at each moment, the blood flow at each moment of process is entirely filled by blood vessel
Amount can calculate the blood flow micro component at each moment, and formula is as follows:
By calculating the blood flow micro component at each moment and the ratio of maximum blood flow micro component, that is, calculate the blood at each moment
Differential score FFD is flowed, the blood vessel entirely change procedure of blood flow during the filling process is obtained, can be commented from the change procedure of blood flow
Estimate and apparent reduction has occurred in sometime blood flow, so that stenosis of the assessment in the vessel position at the moment, calculates
The formula of blood flow differential score is as follows:
Step 13: by the blood flow differential score of blood vessel, dynamic evaluation blood vessel entire during the filling process narrow moment,
Narrow positions, stenosis；
Blood flow reserve score (Fractional Flow Reserve, FFR) is by calculating blood vessel proximally and distally
The ratio of blood pressure obtains, thus to judge between blood vessel proximal end and distal end with the presence or absence of narrow and stenosis, blood flow differential point
Number (Fractional Flow Differential Coefficient, FFD) is by calculating the blood of blood vessel proximally and distally
The ratio of stream micro component obtains, to judge blood vessel with the presence or absence of narrow and stenosis, FFR and FFD can determine whether blood vessel
Stenosis, FFR is based on blood pressure, FFD is based on blood flow variation；
Blood flow differential score provides for hemadostewnosis degree than relatively straightforward evaluation criteria, as blood flow differential score FFD
When > 0.80, hemadostewnosis degree is indicated within an acceptable range, as blood flow differential score FFD < 0.70, indicate that blood vessel is narrow
The risk of narrow degree may be higher, when blood flow differential score FFD is in 0.70~0.80 range, indicates that hemadostewnosis degree needs
It further looks at.
Blood flow differential score can also be used to the recovery extent of assessment post-surgical vascular.
Embodiment 2
A kind of image data processing system of the invention, at a kind of angiogram data for executing embodiment 1
Reason method, the processing unit include:
Digital subtraction angiography machine obtains a series of image datas of blood vessel for executing step 1；
Image receiver module connects digital subtraction angiography machine, for executing step 2, receives contrastographic picture, and press
The format needed according to the device is converted to First ray image IK, M × N, wherein K indicates that image sequence frame number, M indicate every frame image
Horizontal pixel number, N indicate every frame image longitudinal direction number of pixels；Specifically, image receiver module includes and Digital Subtraction blood vessel
The image transmitting interface of contrast machine connection, for the received cable of image, image receiving interface and image converter etc.；Image turns
Parallel operation is the processing unit by the image data of digital subtraction angiography machine transmission according to specified Data Format Transform, such as is schemed
As capture card etc.；
Image storage module connects image receiver module, for executing step 3, stores IK, M × N,；Specifically, image is deposited
Storage module includes control logic, physical storage medium etc., such as image storage software, memory, hard disk etc.；
Human-machine interface module connects image storage module, for executing step 4, shows IK, M × N；Operator can lead to
It crosses human-machine interface module and determines blood vessel proximally and distally in the area-of-interest of image, according to the form of blood vessel and variation feelings
Blood vessel proximal end is determined as normal blood flow by place, blood vessel distal end is determined as hemadostewnosis position by condition；Specifically, human-machine interface
Mouth mold block includes display, printer, user interface, mouse and keyboard etc.；
Image processing module connects image storage module and human-machine interface module, for executing step 5 to step 12,
To IK, M × NIt is handled, calculates blood flow differential parameter, obtain blood flow differential score；Specifically, image processing module includes control
Logic, image processing logic, physical processing unit etc., such as CPU, GPU, NPU, image processing software etc.；
Wherein, image storage module be also used to store by image data, blood flow differential fractional data and the two it
Between process data, human-machine interface module be also used to export display blood flow differential score.
As a preferred embodiment of the present embodiment, after human-machine interface module can show the processing of blood vessel sequential image data
Clearly independent blood-vessel image.
As a preferred embodiment of the present embodiment, human-machine interface module can show virtual blood vessel 3-D image.
Embodiment 3
A kind of image display method of the invention, with the difference of color come the additional size for indicating vascular flow differential score
Degree.
Blood flow differential score is obtained according to the processing method of such as embodiment 1, blood flow differential score is more than or equal to 0.00,
And it is less than or equal to 1.00.
It is red with indicating the corresponding blood flow differential fraction range from the transition color of red, orange, yellow, green, blue, blue, purple
Color, the orange degree for representing blood flow differential score and being lower than 0.70, indicate that the risk of hemadostewnosis degree may be higher, with yellow generation
Table blood flow differential score represents 0.80~1.00 degree, color with green, cyan, blue, purple in 0.70~0.80 degree
It is shown on blood-vessel image or is shown in blood flow differential score numerically.
Embodiment 4
A kind of computer readable storage medium of the invention, is stored thereon with computer program, which is held by processor
The processing method such as embodiment 1 is realized when row or realizes the display methods such as embodiment 3.
Embodiment 5
A kind of electronic equipment of the invention, comprising:
Memory is stored thereon with computer program；
Processor, for executing the program in memory, to realize the processing method such as embodiment 1 or realize as implemented
The display methods of example 3.
As a preferred embodiment of the present embodiment, which may include: processor, memory, which sets
Standby can also include multimedia component, input/output (I/O) one or more of interface and communication component.
Wherein, processor is used to control the integrated operation of the electronic equipment, to complete above-mentioned processing method or above-mentioned aobvious
Show all or part of the steps in method.
For memory for storing various types of data to support the operation in the electronic equipment, these data for example can be with
The relevant data of instruction and application program including any application or method for operating on the electronic equipment；
Memory can be realized by any kind of volatibility or non-volatile memory device or their combination, such as static random
It accesses memory (Static Random Access Memory, SRAM), electrically erasable programmable read-only memory
(Electrically Erasable Programmable Read-Only Memory, EEPROM), erasable programmable is read-only
Memory (Erasable Programmable Read-Only Memory, EPROM), programmable read only memory
(Programmable Read-Only Memory, PROM), read-only memory (Read-Only Memory, ROM), magnetic storage
Device, flash memory, disk or CD.
Multimedia component may include screen and audio component, and wherein screen for example can be touch screen, and audio component is used
In output and/or input audio signal；For example, audio component may include a microphone, microphone is for receiving external sound
Frequency signal, the received audio signal can be further stored in memory or be sent by communication component；Audio component is also
Including at least one loudspeaker, it to be used for output audio signal.
I/O interface provides interface between processor and other interface modules, other above-mentioned interface modules can be keyboard,
Mouse, button etc.；These buttons can be virtual push button or entity button.
Communication component is for carrying out wired or wireless communication between the electronic equipment and other equipment；Wireless communication, such as
Wi-Fi, bluetooth, near-field communication (Near Field Communication, NFC), 2G, 3G, 4G or 5G or they one of
Or several combinations, therefore the corresponding communication component may include: Wi-Fi module, bluetooth module, NFC module, mobile communication
Module.
As a preferred embodiment of the present embodiment, which can be by one or more application specific integrated circuit
(Application Specific Integrated Circuit, ASIC), digital signal processor (Digital Signal
Processor, DSP), it is digital signal processing appts (Digital Signal Processing Device, DSPD), programmable
Logical device (Programmable Logic Device, PLD), field programmable gate array (Field Programmable
Gate Array, FPGA), controller, microcontroller, microprocessor or other electronic components realize, for executing above-mentioned processing
Method or above-mentioned display method.
In addition, the computer readable storage medium that the embodiment of the present disclosure provides can be for above-mentioned depositing including program instruction
Reservoir, above procedure instruction can be executed by the processor of electronic equipment to complete above-mentioned processing method or above-mentioned display method.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (10)
1. a kind of angiogram data processing method, which is characterized in that
The angiographic sequence image data in predetermined amount of time is extracted, the sequential image data includes several frames, described pre-
Section of fixing time includes at least one angioplerosis period；
According to the time interval of amount of pixel change and the frame in the sequence image, the frame of angioplerosis process is calculated
The blood flow at corresponding moment；
Calculate the blood flow differential score of the blood flow relative time at the corresponding moment.
2. processing method according to claim 1, which is characterized in that
Include the steps that the image real time transfer of angiography being the sequential image data；
Include the steps that carrying out de-noising, image enhancement, image recognition to the sequence image；
Include the steps that being formed the new sequence image that blood flow in blood vessel fills process by frame image every in the sequence image；
Including calculating the time interval in the new sequence image between every frame image, according to the new sequence image middle finger
Some fixed cross sections calculate the cross section in the amount of pixel change of several consecutive frame blood-vessel images, pass through the picture
The step of plain variable quantity and the time interval calculate the blood flow of the cross section；
The blood flow including entirely filling each moment of process by blood vessel calculates the blood flow differential at blood vessel each moment
The step of score.
3. processing method according to claim 2, which comprises the following steps:
A, angiography obtains a series of described image data of blood vessel, it is converted to First ray figure according to unified format
As IK, M × N, wherein K indicates that image sequence frame number, M indicate every frame image horizontal pixel number, and IV indicates every frame image longitudinal direction picture
Plain number；
B, blood vessel is determined proximally and distally in the area-of-interest of image, according to the form and situation of change of blood vessel, by blood
Pipe proximal end is determined as normal blood flow by place, and blood vessel distal end is determined as hemadostewnosis position；
C, using Laplace transform and/or using the non-linear filtering method based on partial differential equation to the IK, M × NDisappear
It makes an uproar processing；
D, it is handled and/or using self-adapting histogram equilibrium method using edge sharpening to the IK, M × NIt carries out at image enhancement
Reason, improves the identification of blood vessel；
E, using Scale invariant features transform to the IK, M × NCarry out the transformation and reduction of several scales；
F, to I described after reductionK, M × NIn every frame image carry out image gray processing, image enhancement, image recognition processing, formed blood
Blood flow fills the second sequence image V of process in pipeK, M × N, wherein K indicates that image sequence frame number, M indicate every frame image transverse direction picture
Plain number, N indicate every frame image longitudinal direction number of pixels；
G, the time interval of picture frame where contrast agent picture frame where the blood vessel proximal end reaches the blood vessel distal end is calculated
And frame number can calculate the time interval T between every frame image by time interval and sequence image frame numberK；
H, in the VK, M × NIn specify some described cross section, calculate the cross section in the picture of several consecutive frame blood-vessel images
Plain variable quantity passes through the amount of pixel change and the TKThe cross section is calculated in the blood flow of the period；
I, the blood flow differential for calculating each moment, the blood flow that each moment of process is entirely filled by blood vessel calculate often
The blood flow micro component at a moment calculates the blood flow micro component at each moment and the ratio of the maximum blood flow micro component, i.e.,
Calculate the blood flow differential score at each moment.
4. processing method according to claim 3, which is characterized in that after executing the step B, first to the IK, M × NIt carries out
Gray processing processing, then execute the step C.
5. according to the described in any item processing methods of claim 3-4, which is characterized in that the step E the following steps are included:
E1, to the IK, M × NConvolution algorithm is carried out with Gaussian kernel, the difference of variance is selected according to Gaussian kernel, constitutes different scale ginseng
Several images；
E2, to the IK, M × NIn every frame image carry out several hierarchical transformations, in each hierarchical transformation, among original image
Every extracting pixel, new image is formed, the first transform sequence image is generated after final hierarchical transformation；
E3, several level reduction are carried out to every frame image in the first transform sequence image, in each hierarchical transformation, from
Pixel is sequentially extracted in original image, interval forms new image, adjacent by its to pixel not set in new image
Pixel carries out linear interpolation and obtains, and generates the second transform sequence image after final level reduction.
6. a kind of image data processing system characterized by comprising
Image receiver module is sequence image for receiving a series of images data of blood vessel, and by described image data processing；
Image processing module forms blood flow in blood vessel for carrying out de-noising, image enhancement, image recognition to the sequence image
The new sequence image of full process, according to the time interval between frame image every in new sequence image and some blood specified
In the amount of pixel change of several consecutive frame blood-vessel images the blood flow of the cross section is calculated, according to described in pipe cross section
The blood flow differential score at blood flow calculating blood vessel each moment；
Human-machine interface module, for showing the sequence image and the blood flow differential score.
7. processing unit according to claim 6, which is characterized in that further include image storage module, described image storage
Module is for storing described image data, the sequence image, the new sequence image and the blood flow differential score.
8. a kind of image display method, which is characterized in that obtained according to processing method as described in any one in claim 1-5
The blood flow differential score indicates the corresponding blood flow differential point with from the transition color of red, orange, yellow, green, blue, blue, purple
Number range, the blood flow differential score is more than or equal to 0.00, and is less than or equal to 1.00, represents the blood flow with red
Differential score is lower than 0.70 degree, represents the blood flow differential score close to 1.00 degree with purple.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
Processing method as described in any one in claim 1-5 is realized when row or realizes display methods as claimed in claim 8.
10. a kind of electronic equipment characterized by comprising
Memory is stored thereon with computer program；
Processor, for executing the described program in the memory, to realize processing as described in any one in claim 1-5
Method realizes display methods as claimed in claim 8.
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