CN109345585A - A kind of measurement method and system of the Morphologic Parameters of intracranial aneurysm image - Google Patents
A kind of measurement method and system of the Morphologic Parameters of intracranial aneurysm image Download PDFInfo
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Abstract
This specification embodiment provides the measurement method and system of a kind of Morphologic Parameters of intracranial aneurysm image.This specification embodiment solves the problems, such as that the morphological measurement of intracranial aneurysm image cannot achieve all automatic measurement, measurement consistency is difficult to ensure by the measurement of the Morphologic Parameters of intracranial aneurysm image.The measurement method includes: from the three-dimensional DICOM data of MRA, and segmentation encephalic carries tumor blood-vessel image；Divide intracranial aneurysm image；The Morphologic Parameters of intracranial aneurysm image are measured.The measurement method and system of the Morphologic Parameters for the intracranial aneurysm image that this specification embodiment provides, it can be realized the automation of intracranial aneurysm image measurement, the quickly Morphologic Parameters of measurement intracranial aneurysm image, guarantee the consistency of the morphological measurement result of aneurysm image.
Description
Technical field
This specification is related to field of medical imaging more particularly to a kind of measurement of the Morphologic Parameters of intracranial aneurysm image
Method and system.
Background technique
Intracranial aneurysm is a kind of strumae of the arterial wall caused by the expansion of the local anomaly of entocranial artery inner cavity, is one
The common vascular conditions of kind.It is reported that encephalic Unruptured aneurysm illness rate in China adult is up to 7%, made after rupture
At subarachnoid hemorrhage, handicap or death can lead to.National statistics office data is shown within 2014, and acute cerebrovascular disease is
The second largest cause of death of China human mortality.Aneurismal subarachnoid hemorrhage be after in ischemic cerebral apoplexy and hypertensive cerebral hemorrhage it
The most common acute cerebrovascular diseases afterwards, dead residual rate are up to 64%, about 15% patient's pre hospital time, different economy level of development
The Level of first-aid treatment in area is widely different, has become one of the most common reason for causing China's death.It can be seen that not breaking
Split the wind that is timely and effectively can significantly reducing the following disease hair of aneurysm carrier of aneurysm screening and prevention work
Danger.
In the prior art, the measurement of intracranial aneurysm image, using computer manual measurement, is surveyed substantially by there is experience personnel
Measure speed it is slow, measurement result randomness is big, and accuracy is undesirable, and which can only measure simple parameter, as line segment away from
From；For complex parameters, such as volume or angle, then manual measurement is very inconvenient, and accuracy is difficult to ensure.Aneurysm measurement
Improve, mainly simulation modelling or the improvement of traditional manual measurement method, cannot achieve aneurysm morphology parameter it is complete from
The measurement of flowing mode, its consistency are difficult to ensure.
Therefore, it is necessary to a kind of automated process of the morphological measurement of intracranial aneurysm image, being capable of rapid survey cranium
Internal aneurysm Morphologic Parameters.
Summary of the invention
This specification embodiment provides the measurement method and system of a kind of Morphologic Parameters of intracranial aneurysm image, is used for
It solves following technical problem: can quickly measure the Morphologic Parameters of intracranial aneurysm image, guarantee aneurysm morphology ginseng
The consistency of number measurement result.
In order to solve the above technical problems, this specification embodiment is achieved in that
A kind of measurement method of the Morphologic Parameters for intracranial aneurysm image that this specification embodiment provides, including it is following
Step:
From the three-dimensional DICOM data of MRA, segmentation encephalic carries tumor blood-vessel image；
It is carried on tumor blood-vessel image in the encephalic, divides intracranial aneurysm image；
The Morphologic Parameters of the intracranial aneurysm image are measured.
Further, from the three-dimensional DICOM data of MRA, tonal range is chosen, segmentation encephalic carries tumor blood-vessel image.
Further, on the encephalic parent artery blood-vessel image, the center line and radius of parent artery blood vessel are calculated,
Divide intracranial aneurysm image.
Further, using the intracranial aneurysm image divided and obtained, Aneurysmal neck is generated, to intracranial aneurysm
The Morphologic Parameters of image measure.
This specification embodiment provides a kind of measuring system of the Morphologic Parameters of intracranial aneurysm image, including to place an order
Member:
Input interface, the input of the three-dimensional DICOM data for MRA；
Processing workstation realizes the measurement of the Morphologic Parameters of intracranial aneurysm image；
Output unit: the measurement result of the Morphologic Parameters of intracranial aneurysm image is exported.
Further, from the three-dimensional DICOM data of MRA, segmentation encephalic carries tumor blood-vessel image；
It is carried on tumor blood-vessel image in the encephalic, divides intracranial aneurysm image；
The Morphologic Parameters of the intracranial aneurysm image are measured.
Further, from the three-dimensional DICOM data of MRA, tonal range is chosen, segmentation encephalic carries tumor blood-vessel image.
Further, on the encephalic parent artery blood-vessel image, the center line and radius of parent artery blood vessel are calculated,
Divide intracranial aneurysm image.
Further, using the intracranial aneurysm image divided and obtained, Aneurysmal neck is generated, to intracranial aneurysm
The Morphologic Parameters of image measure.
At least one above-mentioned technical solution that this specification embodiment uses can reach following the utility model has the advantages that this specification
Three-dimensional DICOM data of the embodiment based on MRA, realize the automatic measurement of the Morphologic Parameters of intracranial aneurysm image, can
The quickly Morphologic Parameters of measurement intracranial aneurysm image, guarantee the morphological measurement result of intracranial aneurysm image
Consistency.
Detailed description of the invention
In order to illustrate more clearly of this specification embodiment or technical solution in the prior art, below will to embodiment or
Attached drawing needed to be used in the description of the prior art is briefly described, it should be apparent that, the accompanying drawings in the following description is only
The some embodiments recorded in this specification, for those of ordinary skill in the art, in not making the creative labor property
Under the premise of, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of measuring method flow chart of the Morphologic Parameters for intracranial aneurysm image that this specification provides；
Fig. 2 is the segmentation flow chart that a kind of encephalic that this specification provides carries tumor blood-vessel image；
Fig. 3 is a kind of determination method flow diagram of the tonal range for MRA image that this specification provides；
Fig. 4 is a kind of segmentation flow chart for intracranial aneurysm image that this specification provides；
Two o'clock determines minimum rectangle schematic diagram in a kind of two-dimensional space that Fig. 5 provides for this specification；
Minimum rectangle schematic diagrames are determined at 3 points in the two-dimensional space that Fig. 6 provides for this specification；
Fig. 7 is a kind of surface reconstruction flow chart for intracranial aneurysm image that this specification provides；
Fig. 8 is the aneurysm morphology parameter definition schematic diagram that this specification provides；
Fig. 9 is a kind of aneurysm morphology parameter measurement schematic diagram that this specification provides；
Figure 10 is a kind of measuring system schematic diagram for intracranial aneurysm Morphologic Parameters that this specification provides.
Specific embodiment
In order to make those skilled in the art more fully understand the technical solution in this specification, below in conjunction with this explanation
Attached drawing in book embodiment is clearly and completely described the technical solution in this specification embodiment, it is clear that described
Embodiment be merely a part but not all of the embodiments of the present application.Based on this specification embodiment, this field
Those of ordinary skill's every other embodiment obtained without creative efforts, all should belong to the application
The range of protection.
Fig. 1 is a kind of process of the measurement method of the Morphologic Parameters for intracranial aneurysm image that this specification provides.
This method comprises:
Step S101: from the three-dimensional DICOM data of MRA, segmentation encephalic carries tumor blood-vessel image.
The morphological parameters of intracranial aneurysm image measure, and the three-dimensional DICOM data for often adopting the MRA of intracranial aneurysm are surveyed
Amount.MRA (Magnetic Resonance Angiography, Magnetic Resonance Angiography) is that one kind makes in X-ray sequence of pictures
Visualization of blood vessels technology.The basic principle is that removing phase effect based on saturation effect, inflow enhancement effect, flowing.MRA is
Presaturation band is placed in the head end of 3D layers of block to be saturated venous blood flow, the arterial blood of reverse flow enters 3D layers of block, because not by
Saturation is to generate MR signal.Be divided into multiple thin layers to excite a thicker volume when scanning, reduce excitation volume thickness with
It reduces and flows into saturation effect, and can guarantee scanning volume range, obtain the thin layer image of several layers of adjacent level, make image clearly,
The fine structure of blood vessel shows that spatial resolution improves.MRA is also gradually moved for encephalic because of the imaging characteristics of its high quality
The diagnosis of arteries and veins vascular lesion.
DICOM is the network communication interface standard an of digital medical image.Dicom standard, which is one group, has DICOM simultaneous
Various grammers, semantic commands and related letter between system may be implemented by the agreement in the agreement that the equipment of capacitive follows jointly
The exchange of breath.The main target of the agreement is the diagnostic message for ensureing patient, treatment information, medical image and other all kinds of phases
Communication can be realized between distinct device and system by closing data.
MRA image is stored as DICOM format file.The file of DICOM format includes image size, height, width, every
The requisite information of the normal images such as pixel byte number also stores a large amount of medical informations such as disease in the data element of data acquisition system
People's name, age, hospital's name, imaging time, check point etc..DICOM data store in order, first in array
The pixel in the byte representation image upper left corner, and the last byte indicates the pixel in the image lower right corner.
Due to by equipment irradiation orientation limited, the MRA effect of intracranial aneurysm can only be it is two-dimensional, the two dimensional image is only
The Morphologic Parameters index of basic intracranial aneurysm image: size, aspect ratio, aneurysmal tilt angle etc. can be collected,
It cannot achieve the measurement of the Morphologic Parameters of complicated intracranial aneurysm image, such as aneurysmal volume.Three dimensional morphology parameter
Measurement, it is more meaningful for the research of the Morphologic Parameters of intracranial aneurysm image.Therefore in order to realize intracranial aneurysm figure
The measurement of the Morphologic Parameters of picture needs that the three-dimensional DICOM data of MRA are further processed, first progress encephalic load
The segmentation of tumor blood-vessel image.
Fig. 2 is the segmentation flow chart that a kind of encephalic that this specification provides carries tumor blood-vessel image, and detailed process includes:
Step S201: from the DICOM data of MRA image, tonal range is chosen.
The determination of tonal range is the subsequent premise for carrying out carrying the segmentation of tumor blood-vessel image.This specification embodiment uses area
The mode of domain growth realizes the determination of tonal range.
Fig. 3 is a kind of determination method flow diagram of the tonal range for MRA image that this specification embodiment provides.Specific packet
It includes:
Step S301: it determines the upper and lower bound of the preliminary tonal range of MRA image, determines seed point.
The maximum value and minimum value for extracting entire MRA image pixel value traverse entire MRA image pixel value, write down pixel
Value is the pixel of maximum value, using the point as the seed point of preliminary region growing method；Pixel value is less than most at the same time
The all pixels value being worth greatly calculates average value, take the average value as the lower limit 1 of preliminary tonal range, pixel maximum is as preliminary
The gray scale upper limit 1.In this specification, seed point can be the starting point of growth, and seed point, which is located at, to be carried on tumor blood vessel.
Step S302: pass through preliminary region growing method, primary segmentation MRA image.
Based on the tonal range and seed point that step S301 is determined, by preliminary region growing method to MRA image
Make primary segmentation, to obtain the image comprising carrying tumor blood vessel pixel.
Step S303: the tonal range lower limit of MRA image is primarily determined.
Using the MRA image of step S302 segmentation as template, the pixel of same position in original image is extracted, calculates original graph
As the mean value of pixel；Meanwhile using the MRA image of above-mentioned segmentation as template, the pixel of same position in background image is extracted, is calculated
The mean value of background image pixels；Using the mean value of original image pixels and the mean of mean of background image pixels as preliminary ash
Spend the lower limit 2 of range.
Step S304: being tonal range with preliminary tonal range lower limit 2 and the preliminary tonal range gray scale upper limit 1, with above-mentioned
Seed point is seed point, passes through the method for region growing, primary segmentation MRA image.
The change of tonal range will affect the MRA image that segmentation obtains.Therefore, it after being changed with above-mentioned tonal range, needs
Re-start MRA image segmentation.
Step S305: it determines preliminary tonal range lower limit, and is judged.
Repeat the determination method of preliminary tonal range lower limit described in step S303, the resulting just step gray scale of n-th circulation
Range lower limit is 2-n.Preliminary tonal range lower limit 2-n and preliminary tonal range lower limit 2- (n-1) are compared, the difference of the two
If the absolute value of value is less than 5, and n is more than or equal to 3, then terminates the circulation；If the absolute value of the difference of the two be more than or equal to 5, or
Person n then enters step S304 less than 3.
Step S306: the tonal range of MRA image is determined.
Using the lower limit 2-n of the obtained preliminary tonal range of step S305 as the lower limit of tonal range, obtained with step S301
Preliminary tonal range the upper limit 1 be tonal range the upper limit, i.e., the maximum point of pixel be tonal range the upper limit.
Step S202: utilizing section two-value method, and segmentation encephalic carries tumor blood-vessel image.
The tonal range determined with step S306 carries out the segmentation that encephalic carries tumor blood-vessel image.If pixel value in MRA image
Gray value within above-mentioned tonal range, then retain, otherwise set 0, thus realize MRA image encephalic carry tumor vessel graph
The segmentation of picture.
Step S102: segmentation intracranial aneurysm image.
The encephalic of step S101 segmentation carries tumor blood-vessel image and further progress is needed to divide, and realizes encephalic to carry on tumor blood vessel and moves
The segmentation of arteries and veins tumor image, the intracranial aneurysm image divided.
Fig. 4 is a kind of segmentation flow chart for intracranial aneurysm image that this specification provides.This method comprises:
Step S401: it is carried on tumor blood-vessel image from encephalic to be split, selected seed point and anchor point.
Tumor blood-vessel image, selected seed point and anchor point are carried using encephalic obtained above.Seed point and anchor point are
The starting point of growth is defined as seed point for the ease of distinguishing by space coordinate, and the point that will be chosen on load tumor blood vessel is defined as
Anchor point.The selection of seed point may be selected in aneurysm body surface face, can also be chosen within artery knurl.And anchor point selects
On the load tumor blood vessel intersected with aneurysm.Since intracranial aneurysm includes conventional side tumor and bifurcated vessels tumor, determine
The selection in site, be according to the type of intracranial aneurysm, using different anchor point choosing methods.For conventional side tumor
Speech needs to provide two o'clock in the upstream and downstream for carrying tumor blood vessel, generally chooses and choose two within the scope of aneurysm 5-10mm
Point；For bifurcated vessels tumor, then need to provide an anchor point in the upstream for carrying tumor blood vessel, downstream provides respectively on each branch
One anchor point, totally three anchor points.Wherein, located upstream point is anchor point 1, and downstream location point is anchor point 2, for
Bifurcated vessels, downstream location point include two anchor points.Anchor point can be placed on carry tumor blood vessel surface or carry tumor blood vessel with
It is inside ok, the two is not different.
Step S402: utilizing above-mentioned seed point and anchor point, carries out image expansion, generates the aneurysm image of expansion.
The interception of partial 3 d image is according to seed point coordinate and anchor point coordinate, and the minimum cuboid determined carries out
The pixel increment of transverse direction and longitudinal direction extends, and makes include whole intracranial aneurysm images after extending, with the length determined after extension
Cube region intercepts partial 3 d image.Although the partial 3 d image includes whole intracranial aneurysm images, due to noise
Influence, which is unfavorable for the segmentation of subsequent aneurysm image, it is therefore desirable to further progress image expansion.With
Above-mentioned seed point is starting point, and after 16 expansions, the aneurysm image of generation can be used for subsequent aneurysm image for topography
Cutting.
Two o'clock determines minimum rectangle schematic diagram in a kind of two-dimensional space that Fig. 5 provides for this specification embodiment.Three
Minimum cuboid is determined according to two anchor points and seed point according to similar approach in dimension space.
Minimum rectangle schematic diagrames are determined at 3 points in a kind of two-dimensional space that Fig. 6 provides for this specification embodiment.Three
In dimension space, minimum cuboid is determined according to three anchor points and seed point according to similar approach.
Step S403: utilizing above-mentioned seed point and anchor point, calculates and carries tumor vessel centerline and radius.
The extraction of tumor vessel centerline is carried, the segmentation of intracranial aneurysm is most important.It is wrapped from the topography of above-mentioned interception
In the load tumor lumen contained, along tumor blood vessel is carried, node-by-node algorithm carries the intracorporal inscribed circle of tumor lumen of vessels, with maximum inscribed circle
Circle center line connecting as the center line for carrying tumor blood vessel between anchor point, using the radius of maximum inscribed circle as the point at load tumor blood vessel
Radius.
Step S404: being based on above-mentioned load tumor vessel centerline and radius, carries out carrying tumor reconstructing blood vessel.
In order to effectively carry out aneurysm segmentation, the reconstruction for carrying tumor blood vessel is carried out.Based on above-mentioned load tumor vessel centerline
And radius, using the radius at the point as radius, carries tumor blood vessel table along center line pixel-level generation using the point on center line as the centre of sphere
Face carries out carrying tumor reconstructing blood vessel.
Step S405: with above-mentioned load tumor blood vessel, aforementioned obtained complete aneurysm image, the artery divided are cut
Tumor image.
It is aforementioned to utilize center line, carried out the reconstruction for carrying tumor blood vessel, with the load tumor blood vessel of reconstruction, cut it is aforementioned obtain it is complete
Whole aneurysm image is realized and carries tumor blood vessel and aneurysmal segmentation, the aneurysm image divided.
Step S406: region growing, the aneurysm image divided are carried out with seed point and the aneurysm image of segmentation.
The aneurysm image of above-mentioned segmentation, since there are obscure boundaries etc. to interfere, it is therefore desirable to further be moved to segmentation
Arteries and veins tumor image is handled, and disturbing factor is removed, to obtain clean, complete aneurysm image.Segmentation obtained above is moved
Arteries and veins tumor image is bianry image, therefore obtains the aneurysm figure of connection using seed point as growing point using the method for region growing
Picture finally obtains the complete aneurysm image of segmentation.
Step S103: the measurement of the Morphologic Parameters of intracranial aneurysm image.
The complete intracranial aneurysm image of the segmentation that step S102 is obtained, can carry out the measurement of Morphologic Parameters.In order to
Convenient for showing, the intracranial aneurysm image of above-mentioned segmentation, it is necessary first to carry out the surface reconstruction of intracranial aneurysm image.
Fig. 7 is a kind of surface reconstruction flow chart for intracranial aneurysm image that this specification provides, which includes:
Step 701: the surface reconstruction of intracranial aneurysm image.
This specification realizes three-dimensional surface reconstruct using MC algorithm (MarchingCubes, marching cubes algorithm).MC is calculated
The basic thought of method is exactly the small cubes three-dimensional data space delamination regular shape, eight vertex of these small cubes
It is made of four pixels each on adjacent layer, handles these small cubes one by one, sort out cube intersected with contour surface
Body, and the method for using interpolation calculates the intersection point of contour surface Yu these small cubes sides, finally according to contour surface and these friendships
Expression is approached for what these pressed that certain way is formed by connecting a contour surface in the relative position of point.3D resurfacing utilizes 3D
Visualization tool Visualization Toolki (VTK) is realized by programming.
Step 702: being smoothed using Windowing Sinc function.
The three-dimensional surface reconstructed using MC algorithm, there are bad, the situations such as data inaccuracy are handled at face joint, therefore
It needs to be smoothed.
Step 703: obtaining the surface data of intracranial aneurysm image.
Based on the three-dimensionalreconstruction of above-mentioned MC algorithm, smoothing processing obtains the surface data of intracranial aneurysm image.
Intracranial aneurysm Morphologic Parameters include Aneurysmal neck, aneurysm diameter, aneurysm height, aneurysm width,
Aneurysm incident angle, aneurysm volume.Wherein, the key parameter of intracranial aneurysm Morphologic Parameters is Aneurysmal neck center
It calculates.
Fig. 8 is aneurysm morphology parameter definition schematic diagram provided in an embodiment of the present invention.It specifically includes as follows:
D (aneurysm major diameter): i.e. aneurysm size is that tumor neck midpoint maximum distance is a little arrived on aneurysm top；
H (aneurysm height): the maximum normal distance of Aneurysmal neck line is a little arrived on aneurysm tumor top；
W (aneurysm width): the maximum distance vertical with aneurysm major diameter；
IA (flows into angle): the angle of aneurysmal major diameter and parent artery central axes；
PV (parent artery diameter):
Sidewall portion: PV=(D1+D2)/2；
Furcation: PV=(D1+D2+D3)/3, Di=(Dia+Dib)/2 (i=1,2,3) this specification embodiment is manual
On the basis of selecting seed point and two anchor points, automatic measurement is realized.
Fig. 9 is a kind of aneurysm morphology parameter measurement schematic diagram that this specification embodiment provides.Specifically, aneurysm
The thinking of parameter measurement is as follows:
In visualization tool VTK, aneurysm surface is intersected with blood vessel surface, is needed the true intersection of the two, cannot be included,
It can not be overlapped, it is therefore desirable to after amplifying aneurysm surface data, just may be implemented really to intersect, obtain intersection.It puts
When big, entire aneurysm surface data is amplified according to three coordinate directions.Amplified aneurysm surface and original blood
Pipe surface intersection, intersection is tumor neck.
According to above-mentioned tumor neck point set, the space geometry center of the point set is calculated, using the geometric center as aneurysm tumor
Neck center, which may not be in aneurysm, and calculates the minimum range on the centre distance aneurysm boundary, is denoted as dmin；
Then the distance average on tumor neck apart from tumor neck center is calculated, using the distance average as tumor neck radius, tumor neck diameter is
2 times of tumor neck radius.
The calculating of tumor cervical approach vector confirms shortest path central point along the center line of parent artery blood vessel, in this path
The line of heart point and tumor neck central point is simultaneously directed toward aneurysmal direction as tumor cervical approach vector.
Projection of the line of point and tumor neck central point in aneurysm on tumor cervical approach vector, takes the maximum value of the projection to make
For aneurysmal height calculations, if tumor neck central point, inside aneurysm, which is used as aneurysmal height
Degree；If tumor neck central point, outside aneurysm, which subtracts the result of above-mentioned dmin as aneurysm height.
The calculating of aneurysm diameter finds the maximum value in aneurysm with tumor neck central point line as aneurysmal diameter
Calculated value, if tumor neck central point, inside aneurysm, which is aneurysm diameter；If tumor neck central point is dynamic
Outside arteries and veins tumor, then the diameter calculation value subtracts the result of above-mentioned dmin as aneurysm diameter.
The calculating of aneurysm width needs first to calculate any two points vertical with aneurysm diametrical direction on aneurysm image
Line distance takes this apart from maximum value as aneurysm width.
The calculating of aneurysm volume needs first to count the pixel number in aneurysm image, then with pixel number
Product with voxel is as aneurysmal volume.
Aneurysm incidence angle calculates, and needs first to calculate on the corresponding center line of parent artery vessel centerline located upstream point
Point, the line of the point and above-mentioned path center point and the angle of aneurysm diameter are aneurysm incidence angle.
Figure 10 is a kind of measuring system of the Morphologic Parameters for intracranial aneurysm image that this specification provides.The system packet
It includes:
Input interface: the input of the three-dimensional DICOM data for MRA；
Processing workstation: the measurement of intracranial aneurysm Morphologic Parameters is realized；
Output unit: the result of intracranial aneurysm Morphologic Parameters is exported.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the movement recorded in detail in the claims or step can be come according to the sequence being different from embodiment
It executes and desired result still may be implemented.In addition, process depicted in the drawing not necessarily require show it is specific suitable
Sequence or consecutive order are just able to achieve desired result.In some embodiments, multitasking and parallel processing be also can
With or may be advantageous.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for device,
For electronic equipment, nonvolatile computer storage media embodiment, since it is substantially similar to the method embodiment, so description
It is fairly simple, the relevent part can refer to the partial explaination of embodiments of method.
Device that this specification embodiment provides, electronic equipment, nonvolatile computer storage media with method are corresponding
, therefore, device, electronic equipment, nonvolatile computer storage media also have the Advantageous effect similar with corresponding method
Fruit, since the advantageous effects of method being described in detail above, which is not described herein again corresponding intrument,
The advantageous effects of electronic equipment, nonvolatile computer storage media.
In the 1990s, the improvement of a technology can be distinguished clearly be on hardware improvement (for example,
Improvement to circuit structures such as diode, transistor, switches) or software on improvement (improvement for method flow).So
And with the development of technology, the improvement of current many method flows can be considered as directly improving for hardware circuit.
Designer nearly all obtains corresponding hardware circuit by the way that improved method flow to be programmed into hardware circuit.Cause
This, it cannot be said that the improvement of a method flow cannot be realized with hardware entities module.For example, programmable logic device
(Programmable Logic Device, PLD) (such as field programmable gate array (Field Programmable Gate
Array, FPGA)) it is exactly such a integrated circuit, logic function determines device programming by user.By designer
Voluntarily programming comes a digital display circuit " integrated " on a piece of PLD, designs and makes without asking chip maker
Dedicated IC chip.Moreover, nowadays, substitution manually makes IC chip, this programming is also used instead mostly " is patrolled
Volume compiler (logic compiler) " software realizes that software compiler used is similar when it writes with program development,
And the source code before compiling also write by handy specific programming language, this is referred to as hardware description language
(Hardware Description Language, HDL), and HDL is also not only a kind of, but there are many kind, such as ABEL
(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description
Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL
(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby
Hardware Description Language) etc., VHDL (Very-High-Speed is most generally used at present
Integrated Circuit Hardware Description Language) and Verilog.Those skilled in the art also answer
This understands, it is only necessary to method flow slightly programming in logic and is programmed into integrated circuit with above-mentioned several hardware description languages,
The hardware circuit for realizing the logical method process can be readily available.
Controller can be implemented in any suitable manner, for example, controller can take such as microprocessor or processing
The computer for the computer readable program code (such as software or firmware) that device and storage can be executed by (micro-) processor can
Read medium, logic gate, switch, specific integrated circuit (Application Specific Integrated Circuit,
ASIC), the form of programmable logic controller (PLC) and insertion microcontroller, the example of controller includes but is not limited to following microcontroller
Device: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320 are deposited
Memory controller is also implemented as a part of the control logic of memory.It is also known in the art that in addition to
Pure computer readable program code mode is realized other than controller, can be made completely by the way that method and step is carried out programming in logic
Controller is obtained to come in fact in the form of logic gate, switch, specific integrated circuit, programmable logic controller (PLC) and insertion microcontroller etc.
Existing identical function.Therefore this controller is considered a kind of hardware component, and to including for realizing various in it
The device of function can also be considered as the structure in hardware component.Or even, it can will be regarded for realizing the device of various functions
For either the software module of implementation method can be the structure in hardware component again.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media play
It is any in device, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or these equipment
The combination of equipment.
For convenience of description, it is divided into various units when description apparatus above with function to describe respectively.Certainly, implementing this
The function of each unit can be realized in the same or multiple software and or hardware when specification one or more embodiment.
It should be understood by those skilled in the art that, this specification embodiment can provide as method, system or computer program
Product.Therefore, this specification embodiment can be used complete hardware embodiment, complete software embodiment or combine software and hardware
The form of the embodiment of aspect.Moreover, it wherein includes that computer is available that this specification embodiment, which can be used in one or more,
It is real in the computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) of program code
The form for the computer program product applied.
This specification is referring to the method, equipment (system) and computer program product according to this specification embodiment
Flowchart and/or the block diagram describes.It should be understood that can be realized by computer program instructions every in flowchart and/or the block diagram
The combination of process and/or box in one process and/or box and flowchart and/or the block diagram.It can provide these computers
Processor of the program instruction to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices
To generate a machine, so that generating use by the instruction that computer or the processor of other programmable data processing devices execute
In the dress for realizing the function of specifying in one or more flows of the flowchart and/or one or more blocks of the block diagram
It sets.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method of element, commodity or equipment.
This specification can describe in the general context of computer-executable instructions executed by a computer, such as journey
Sequence module.Generally, program module include routines performing specific tasks or implementing specific abstract data types, programs, objects,
Component, data structure etc..Specification can also be practiced in a distributed computing environment, in these distributed computing environments,
By executing task by the connected remote processing devices of communication network.In a distributed computing environment, program module can
To be located in the local and remote computer storage media including storage equipment.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.
The foregoing is merely this specification embodiments, are not intended to limit this application.For those skilled in the art
For, various changes and changes are possible in this application.All any modifications made within the spirit and principles of the present application are equal
Replacement, improvement etc., should be included within the scope of the claims of this application.
Claims (9)
1. a kind of measurement method of the Morphologic Parameters of intracranial aneurysm image, which comprises the following steps:
From the three-dimensional DICOM data of MRA, segmentation encephalic carries tumor blood-vessel image；
It is carried on tumor blood-vessel image in the encephalic, divides intracranial aneurysm image；
The Morphologic Parameters of the intracranial aneurysm image are measured.
2. the method as described in claim 1, which is characterized in that in the three-dimensional DICOM data from MRA, segmentation encephalic is carried
Tumor blood-vessel image, specifically includes:
From the three-dimensional DICOM data of MRA, tonal range is chosen, segmentation encephalic carries tumor blood-vessel image.
3. the method as described in claim 1, which is characterized in that it is described to be carried on tumor blood-vessel image in the encephalic, divide encephalic
Aneurysm image, specifically includes:
On the encephalic parent artery blood-vessel image, the center line and radius of parent artery blood vessel are calculated, divides entocranial artery
Tumor image.
4. the method as described in claim 1, which is characterized in that the Morphologic Parameters to the intracranial aneurysm image into
Row measurement, specifically includes:
Using the intracranial aneurysm image divided and obtained, Aneurysmal neck is generated, to the morphology of intracranial aneurysm image
Parameter measures.
5. a kind of measuring system of the Morphologic Parameters of intracranial aneurysm image, which is characterized in that including with lower unit:
Input interface, the input of the three-dimensional DICOM data for MRA；
Processing workstation realizes the measurement of the Morphologic Parameters of intracranial aneurysm image；
Output unit: the measurement result of the Morphologic Parameters of intracranial aneurysm image is exported.
6. system as claimed in claim 5, which is characterized in that the survey of the Morphologic Parameters for realizing intracranial aneurysm image
Amount, specifically includes:
From the three-dimensional DICOM data of MRA, segmentation encephalic carries tumor blood-vessel image；
It is carried on tumor blood-vessel image in the encephalic, divides intracranial aneurysm image；
The Morphologic Parameters of the intracranial aneurysm image are measured.
7. system as claimed in claim 6, which is characterized in that the three-dimensional DICOM data from MRA, segmentation encephalic carry tumor
Blood-vessel image specifically includes:
From the three-dimensional DICOM data of MRA, tonal range is chosen, segmentation encephalic carries tumor blood-vessel image.
8. system as claimed in claim 6, which is characterized in that it is described to be carried on tumor blood-vessel image in the encephalic, divide encephalic
Aneurysm image, specifically includes:
On the encephalic parent artery blood-vessel image, the center line and radius of parent artery blood vessel are calculated, divides entocranial artery
Tumor image.
9. system as claimed in claim 6, which is characterized in that the Morphologic Parameters to the intracranial aneurysm image into
Row measurement, specifically includes:
Using the intracranial aneurysm image divided and obtained, Aneurysmal neck is generated, to the morphology of intracranial aneurysm image
Parameter measures.
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| PCT/CN2019/113268 WO2020083374A1 (en) | 2018-10-26 | 2019-10-25 | Method and system for measuring morphological parameters of an intracranial aneurysm image |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020083374A1 (en) * | 2018-10-26 | 2020-04-30 | Union Strong (Beijing) Technology Co. Ltd. | Method and system for measuring morphological parameters of an intracranial aneurysm image |
| WO2020083375A1 (en) * | 2018-10-26 | 2020-04-30 | Union Strong (Beijing) Technology Co. Ltd. | Method and System for Measuring Morphological Parameters of An Intracranial Aneurysm Image |
| CN111462047A (en) * | 2020-03-06 | 2020-07-28 | 深圳睿心智能医疗科技有限公司 | Blood vessel parameter measuring method, blood vessel parameter measuring device, computer equipment and storage medium |
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040193006A1 (en) * | 1995-07-24 | 2004-09-30 | Chen David T. | Anatomical visualization system |
| CN1973301A (en) * | 2004-06-23 | 2007-05-30 | 皇家飞利浦电子股份有限公司 | Image processing system for displaying information relating to parameters of a 3-D tubular object |
| CN101290685A (en) * | 2007-04-20 | 2008-10-22 | 美国西门子医疗解决公司 | Coronary artery three-dimensional modeling |
| CN101923607A (en) * | 2010-09-01 | 2010-12-22 | 冯睿 | Blood vessel computer aided iconography evaluating system |
| CN102239495A (en) * | 2008-12-04 | 2011-11-09 | 皇家飞利浦电子股份有限公司 | A method, apparatus, and computer program product for acquiring medical image data |
| US20120323547A1 (en) * | 2011-06-20 | 2012-12-20 | Siemens Corporation | Method for intracranial aneurysm analysis and endovascular intervention planning |
| US20150238199A1 (en) * | 2014-02-27 | 2015-08-27 | Incumedx, Inc. | Embolic framing microcoils |
| CN107273658A (en) * | 2017-05-16 | 2017-10-20 | 哈尔滨医科大学 | Rupture of intracranial aneurysm risk is estimated and its device that image is classified |
| CN107468334A (en) * | 2017-08-01 | 2017-12-15 | 强联智创（北京）科技有限公司 | A kind of moulding aided design system of three-dimensional microtubular and design method |
| CN107847207A (en) * | 2015-07-09 | 2018-03-27 | Pentas股份有限公司 | Blood-vessel image processing unit, blood-vessel image processing routine and blood-vessel image processing method |
| CN108030550A (en) * | 2017-12-26 | 2018-05-15 | 成都真实维度科技有限公司 | A kind of aneurysmal knurl neck angle computation method based on virtual image |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050259854A1 (en) * | 2004-05-21 | 2005-11-24 | University Of Chicago | Method for detection of abnormalities in three-dimensional imaging data |
| US20080172073A1 (en) * | 2006-06-16 | 2008-07-17 | Searete Llc, A Limited Liability Corporation Of The State Of Delaware | Active blood vessel sleeve |
| JP2011104206A (en) * | 2009-11-19 | 2011-06-02 | Hiroshima City Univ | Aneurysm candidate detection support device and detecting method |
| CN106709920B (en) * | 2016-12-15 | 2021-01-12 | 上海联影医疗科技股份有限公司 | Blood vessel extraction method and device |
| CN106683549A (en) * | 2016-12-13 | 2017-05-17 | 李翔宇 | Aneurysm model based on 3D printing and manufacturing method thereof |
| CN107049484A (en) * | 2017-01-21 | 2017-08-18 | 绍兴市人民医院 | Intracranial aneurysm 3D model Method of printings based on DSA data |
| CN109345585B (en) * | 2018-10-26 | 2021-11-30 | 强联智创（北京）科技有限公司 | Method and system for measuring morphological parameters of intracranial aneurysm image |
| CN109447967B (en) * | 2018-10-26 | 2022-03-01 | 强联智创（北京）科技有限公司 | Method and system for segmenting intracranial aneurysm image |
| CN109389637B (en) * | 2018-10-26 | 2021-12-21 | 强联智创（北京）科技有限公司 | Method and system for measuring morphological parameters of intracranial aneurysm image |
-
2018
- 2018-10-26 CN CN201811260353.XA patent/CN109345585B/en active Active
-
2019
- 2019-10-25 WO PCT/CN2019/113268 patent/WO2020083374A1/en active Application Filing
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040193006A1 (en) * | 1995-07-24 | 2004-09-30 | Chen David T. | Anatomical visualization system |
| CN1973301A (en) * | 2004-06-23 | 2007-05-30 | 皇家飞利浦电子股份有限公司 | Image processing system for displaying information relating to parameters of a 3-D tubular object |
| CN101290685A (en) * | 2007-04-20 | 2008-10-22 | 美国西门子医疗解决公司 | Coronary artery three-dimensional modeling |
| CN102239495A (en) * | 2008-12-04 | 2011-11-09 | 皇家飞利浦电子股份有限公司 | A method, apparatus, and computer program product for acquiring medical image data |
| CN101923607A (en) * | 2010-09-01 | 2010-12-22 | 冯睿 | Blood vessel computer aided iconography evaluating system |
| US20120323547A1 (en) * | 2011-06-20 | 2012-12-20 | Siemens Corporation | Method for intracranial aneurysm analysis and endovascular intervention planning |
| US20150238199A1 (en) * | 2014-02-27 | 2015-08-27 | Incumedx, Inc. | Embolic framing microcoils |
| CN107847207A (en) * | 2015-07-09 | 2018-03-27 | Pentas股份有限公司 | Blood-vessel image processing unit, blood-vessel image processing routine and blood-vessel image processing method |
| CN107273658A (en) * | 2017-05-16 | 2017-10-20 | 哈尔滨医科大学 | Rupture of intracranial aneurysm risk is estimated and its device that image is classified |
| CN107468334A (en) * | 2017-08-01 | 2017-12-15 | 强联智创（北京）科技有限公司 | A kind of moulding aided design system of three-dimensional microtubular and design method |
| CN108030550A (en) * | 2017-12-26 | 2018-05-15 | 成都真实维度科技有限公司 | A kind of aneurysmal knurl neck angle computation method based on virtual image |
Non-Patent Citations (1)
| Title |
|---|
| 谭世芳等: "前交通动脉瘤破裂的形态学因素研究进展", 《中国实用医药》 * |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020083375A1 (en) * | 2018-10-26 | 2020-04-30 | Union Strong (Beijing) Technology Co. Ltd. | Method and System for Measuring Morphological Parameters of An Intracranial Aneurysm Image |
| WO2020083374A1 (en) * | 2018-10-26 | 2020-04-30 | Union Strong (Beijing) Technology Co. Ltd. | Method and system for measuring morphological parameters of an intracranial aneurysm image |
| US11875503B2 (en) | 2018-10-26 | 2024-01-16 | Union Strong (Beijing) Technology Co. Ltd. | Method and system for measuring morphological parameters of an intracranial aneurysm image |
| CN111462047A (en) * | 2020-03-06 | 2020-07-28 | 深圳睿心智能医疗科技有限公司 | Blood vessel parameter measuring method, blood vessel parameter measuring device, computer equipment and storage medium |
| CN111462047B (en) * | 2020-03-06 | 2024-03-12 | 深圳睿心智能医疗科技有限公司 | Vascular parameter measurement method, vascular parameter measurement device, vascular parameter measurement computer device and vascular parameter measurement storage medium |
| CN111513739A (en) * | 2020-04-10 | 2020-08-11 | 北京东软医疗设备有限公司 | Control method and device for angiography machine, electronic device and storage medium |
| CN111513739B (en) * | 2020-04-10 | 2023-08-29 | 北京东软医疗设备有限公司 | Angiography machine control method and device, electronic device and storage medium |
| CN112102333B (en) * | 2020-09-02 | 2022-11-04 | 合肥工业大学 | Ultrasonic region segmentation method and system for B-ultrasonic DICOM (digital imaging and communications in medicine) image |
| CN112102333A (en) * | 2020-09-02 | 2020-12-18 | 合肥工业大学 | Ultrasonic region segmentation method and system for B-ultrasonic DICOM (digital imaging and communications in medicine) image |
| CN113100801A (en) * | 2021-04-14 | 2021-07-13 | 清华大学 | Method and device for determining incident angle of aneurysm, electronic device and storage medium |
| CN113298830A (en) * | 2021-06-22 | 2021-08-24 | 西南大学 | Acute intracranial ICH region image segmentation method based on self-supervision |
| CN114010216A (en) * | 2021-12-20 | 2022-02-08 | 重庆医科大学附属第一医院 | Airway morphological parameter quantitative acquisition method and device and airway stent design method |
| CN114266767B (en) * | 2022-01-27 | 2022-08-23 | 深圳市铱硙医疗科技有限公司 | Method and device for measuring morphological parameters of intracranial aneurysm image |
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| WO2020083374A1 (en) | 2020-04-30 |
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