CN109584261A - A kind of dividing method and system of intracranial aneurysm image - Google Patents
A kind of dividing method and system of intracranial aneurysm image Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/155—Segmentation; Edge detection involving morphological operators
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/187—Segmentation; Edge detection involving region growing; involving region merging; involving connected component labelling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/64—Analysis of geometric attributes of convexity or concavity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10116—X-ray image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30096—Tumor; Lesion
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
- G06T2207/30101—Blood vessel; Artery; Vein; Vascular
Abstract
This specification embodiment provides the dividing method and system of a kind of intracranial aneurysm image, this method comprises: carrying on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image；The treelike center line for obtaining the partial 3 d image calculates center line and radius that the encephalic carries tumor blood-vessel image；The center line and radius of tumor blood-vessel image are carried based on the encephalic, carry out the segmentation of intracranial aneurysm image.This method provides a kind of segmentation precisions preferably, the dividing method of the segmentation higher intracranial aneurysm image of efficiency, realizes the automatic segmentation of intracranial aneurysm image.
Description
Technical field
This specification is related to field of medical imaging more particularly to a kind of dividing method and system of intracranial aneurysm image.
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 encephalic
Aneurysmal clinical teaching research, the treatment for intracranial aneurysm have promote meaning.
In the prior art, intracranial aneurysm image is split, removal carries tumor blood-vessel image, and it is dynamic to obtain pure encephalic
Arteries and veins tumor image is split often based on the experience of operator using manual methods, and segmentation precision is lower, and splitting speed is slow.
Therefore, it is necessary to a kind of dividing methods of intracranial aneurysm image, can be improved the segmentation essence of intracranial aneurysm image
Degree and segmentation efficiency.
Summary of the invention
This specification embodiment provides the dividing method and system of a kind of intracranial aneurysm image, for solving following technology
Problem: intracranial aneurysm image segmentation precision is low, splitting speed is slow.
In order to solve the above technical problems, this specification embodiment is achieved in that
The dividing method for a kind of intracranial aneurysm image that this specification embodiment provides, which is characterized in that including following
Step:
It is carried on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image；
The treelike center line for obtaining the partial 3 d image calculates the center line and half that the encephalic carries tumor blood-vessel image
Diameter；
The center line and radius of tumor blood-vessel image are carried based on the encephalic, carry out the segmentation of intracranial aneurysm image.
Further, described to be carried on tumor blood-vessel image from encephalic to be split, partial 3 d image is intercepted, is specifically included:
It is carried on tumor blood-vessel image from encephalic to be split, determines seed point coordinate and anchor point coordinate；
According to seed point coordinate and anchor point coordinate, partial 3 d image is intercepted.
Further, the treelike center line for obtaining the partial 3 d image calculates the encephalic and carries tumor vessel graph
The center line and radius of picture, specifically include:
Using look-up table, the point in the partial 3 d image is deleted, obtains the tree of the partial 3 d image
Shape center line；
Along the treelike center line, the shortest path between described two anchor points is calculated, carries tumor blood-vessel image as encephalic
Center line；
The center line of tumor blood-vessel image is carried along the encephalic, node-by-node algorithm vessel borders carry tumor vessel graph apart from the encephalic
The shortest distance of the center line of picture carries the radius of every bit on tumor blood-vessel image center line as encephalic.
Further, the center line and radius that tumor blood-vessel image is carried based on the encephalic, carries out intracranial aneurysm figure
The segmentation of picture, specifically includes:
Using the treelike center line and the seed point coordinate of the partial 3 d image, morphological dilations are carried out, then
It carries tumor blood-vessel image using the encephalic to be split to be split the result images of expansion, the intracranial aneurysm expanded
Image；
The center line that tumor blood-vessel image is carried along the encephalic, using the weighted value of encephalic load tumor blood-vessel image radius as distance
Threshold value is split the intracranial aneurysm image of the expansion；
Intracranial aneurysm image after segmentation is rebuild, the intracranial aneurysm image divided.
Further, the center line that tumor blood-vessel image is carried along the encephalic carries tumor blood-vessel image radius with encephalic
Weighted value is split the intracranial aneurysm image of the expansion, specifically includes as distance threshold:
The center line that tumor blood-vessel image is carried along the encephalic carries 1.1 times of radius of tumor blood-vessel image as cranium using encephalic
Contain the weighted value of tumor blood-vessel image radius；
Using the weighted value of encephalic load tumor blood-vessel image radius as distance threshold, by what is generated within the scope of distance threshold
Intracranial aneurysm image is reset, and realizes the segmentation to the intracranial aneurysm image of the expansion.
Further, the intracranial aneurysm image after described pair of segmentation is rebuild, the intracranial aneurysm figure divided
Picture specifically includes:
The intracranial aneurysm image after segmentation is rebuild, is obtained using region growing method using seed point coordinate
The intracranial aneurysm image of segmentation.
This specification embodiment provides a kind of segmenting system of intracranial aneurysm image, comprising:
Input interface carries the input of tumor blood-vessel image for encephalic to be split；
Processing workstation carries the center line and radius of tumor blood-vessel image based on encephalic, carries out point of intracranial aneurysm image
It cuts；
Output unit exports the intracranial aneurysm image of segmentation.
Further, the center line and radius that tumor blood-vessel image is carried based on encephalic, carries out intracranial aneurysm image
Segmentation, specifically includes:
It is carried on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image；
The treelike center line for obtaining the partial 3 d image calculates the center line and half that the encephalic carries tumor blood-vessel image
Diameter；
The center line and radius of tumor blood-vessel image are carried based on the encephalic, carry out the segmentation of intracranial aneurysm image.
Further, described to be carried on tumor blood-vessel image from encephalic to be split, partial 3 d image is intercepted, is specifically included:
It is carried on tumor blood-vessel image from encephalic to be split, determines seed point coordinate and anchor point coordinate；
According to seed point coordinate and anchor point coordinate, partial 3 d image is intercepted.
Further, the treelike center line for obtaining the partial 3 d image calculates the encephalic and carries tumor vessel graph
The center line and radius of picture, specifically include:
Using look-up table, the point in the partial 3 d image is deleted, obtains the tree of the partial 3 d image
Shape center line；
Along the treelike center line, the shortest path between described two anchor points is calculated, carries tumor blood-vessel image as encephalic
Center line；
The center line of tumor blood-vessel image is carried along the encephalic, node-by-node algorithm vessel borders carry tumor vessel graph apart from the encephalic
The shortest distance of the center line of picture carries the radius of every bit on tumor blood-vessel image center line as encephalic.
Further, the center line and radius that tumor blood-vessel image is carried based on the encephalic, carries out intracranial aneurysm figure
The segmentation of picture, specifically includes:
Using the treelike center line and the seed point coordinate of the partial 3 d image, morphological dilations are carried out, then
It carries tumor blood-vessel image using the encephalic to be split to be split the result images of expansion, the intracranial aneurysm expanded
Image；
The center line that tumor blood-vessel image is carried along the encephalic, using the weighted value of encephalic load tumor blood-vessel image radius as distance
Threshold value is split the intracranial aneurysm image of the expansion；
Intracranial aneurysm image after segmentation is rebuild, the intracranial aneurysm image divided.
Further, the center line that tumor blood-vessel image is carried along the encephalic carries tumor blood-vessel image radius with encephalic
Weighted value is split the intracranial aneurysm image of the expansion, specifically includes as distance threshold:
The center line that tumor blood-vessel image is carried along the encephalic carries 1.1 times of radius of tumor blood-vessel image as cranium using encephalic
Contain the weighted value of tumor blood-vessel image radius；
Using the weighted value of encephalic load tumor blood-vessel image radius as distance threshold, by what is generated within the scope of distance threshold
Intracranial aneurysm image is reset, and realizes the segmentation to the intracranial aneurysm image of the expansion.
Further, the intracranial aneurysm image after described pair of segmentation is rebuild, the intracranial aneurysm figure divided
Picture specifically includes:
The intracranial aneurysm image after segmentation is rebuild, is obtained using region growing method using seed point coordinate
The intracranial aneurysm image of segmentation.
At least one above-mentioned technical solution that this specification embodiment uses can reach following effective effect: this specification
Embodiment uses the partitioning algorithm based on center line, realizes the automatic segmentation of intracranial aneurysm image, can quickly carry out encephalic
The automatic segmentation of aneurysm image improves intracranial aneurysm image segmentation precision and segmentation efficiency.
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 schematic diagram of the dividing method 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. 2 provides for this specification；
Minimum rectangle schematic diagrames are determined at 3 points in a kind of two-dimensional space that Fig. 3 provides for this specification；
Fig. 4 is a kind of effect diagram of the dividing method for intracranial aneurysm image that this specification provides；
Fig. 5 is a kind of flow chart of the dividing method for intracranial aneurysm image that this specification provides；
How Fig. 6 judges that certain point whether can when obtaining the treelike center line of partial 3 d image for what this specification provided
It deletes；
Fig. 7 is a kind of schematic diagram of the segmenting system for intracranial aneurysm image 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 schematic diagram of the dividing method for intracranial aneurysm image that this specification provides.This method comprises:
Step S101: carrying on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image.
DSA and MRA image is common intracranial aneurysm image, but due to containing have powerful connections equal disturbing factors in the image,
It is unfavorable for being studied in clinic, therefore, it is necessary to carry out the processing of intracranial aneurysm image.
DSA (Digital Subtraction Angiography, Technology of Digital Subtraction Angiography) is that one kind penetrates X
The technology of visualization of blood vessels in line sequence of pictures.The basic principle is that the two frame X ray pictures shot before and after contrast agent will be injected
As being digitized input picture computer, clearly pure blood vessel image is obtained by subtracting shadow, enhancing and reimaging process, simultaneously
Blood vessel shadow is presented in real time.DSA technology is other detection methods in terms of picture quality, judging blood flow direction and advantage
It cannot compare, therefore " goldstandard " of referred to as vascular conditions diagnosis.
MRA (Magnetic Resonance Angiography, magnetic resonance angiography), refers to Magnetic Resonance Angiography,
Magnetic resonance can row angiography, that is, show blood vessel, it is possible to find the position of hemadostewnosis and occlusion.The basic principle is that based on full
Phase effect is removed with effect, inflow enhancement effect, flowing.MRA is that presaturation band is placed in the head end of 3D layers of block to be saturated vein
Blood flow, the arterial blood of reverse flow enter 3D layers of block, because not being saturated to generate MR signal.By a thicker appearance when scanning
Integral is cut into multiple thin layer excitations, reduces excitation volume thickness to reduce inflow saturation effect, and can guarantee scanning volume range,
The thin layer image for obtaining several layers of adjacent level makes image clearly, and the fine structure of blood vessel is shown, spatial resolution improves.
The segmentation that encephalic carries tumor blood-vessel image may be implemented by the method for region growing in 3-D image based on DSA,
This method can effectively reduce noise jamming, promote budget efficiency.And the 3-D image based on MRA, pass through the side of section two-value
Method, may be implemented the segmentation that encephalic carries tumor blood-vessel image, and this method can fast and accurately divide encephalic and carry tumor blood-vessel image, make
Vessel borders are more clear.
Tumor blood-vessel image is carried using the encephalic of segmentation obtained by the above method, needs to be further processed, realizes encephalic
The segmentation of aneurysm image on tumor blood vessel is carried, and then carries out the teaching research of intracranial aneurysm.
Tumor blood-vessel image is carried using encephalic obtained above, determines seed point and anchor point.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 image is determined
Justice is anchor point.The selection of seed point may be selected in artery knurl imaging surface, can also be chosen at artery knurl image it
It is interior.And anchor point is selected in above the load tumor blood-vessel image intersected with aneurysm image.Since intracranial aneurysm includes conventional side
Tumor and bifurcated vessels tumor, therefore the determination of anchor point, be according to the type of intracranial aneurysm, using different anchor point determination sides
Method.For conventional side tumor, needs the upstream and downstream for carrying tumor blood vessel in encephalic to provide two o'clock, generally choose from cranium
Two o'clock is chosen within the scope of internal aneurysm image 5-10mm；For bifurcated vessels tumor, then need to carry the upper of tumor blood-vessel image in encephalic
Trip provides an anchor point, and downstream provides an anchor point respectively on each branch, totally three anchor points.Wherein, upstream
Anchor point is anchor point 1, and downstream location point is anchor point 2, and for bifurcated vessels, downstream location point includes two anchor points.It is fixed
Site can be placed on the surface of encephalic load tumor blood-vessel image or carry and be ok within tumor blood-vessel image, and the two is not different.
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.
Two o'clock determines minimum rectangle schematic diagram in the two-dimensional space that Fig. 2 provides for this specification.It presses in three dimensions
Minimum cuboid is determined according to two anchor points and seed point according to similar approach.
Minimum rectangle schematic diagrames are determined at 3 points in the two-dimensional space that Fig. 3 provides for this specification.In three dimensions, it presses
Minimum cuboid is determined according to three anchor points and seed point according to similar approach.
Step S102: obtaining the treelike center line of the partial 3 d image, calculates the encephalic and carries tumor blood-vessel image
Center line and radius.
Based on the partial 3 d image of step S101 interception, look-up table is further used, in above-mentioned partial 3 d image
Point deleted, the treelike center line of the partial 3 d image can be obtained.The realization process is specific as follows:
Judge that can a point remove with eight consecutive points (eight connectivity)；
From image, remove some points, finally obtains the axis of image, the treelike center of the as described partial 3 d image
Line.
Along the treelike center line of the partial 3 d image of above-mentioned acquisition, the shortest path between two anchor points is calculated, is made
The center line of tumor blood-vessel image is carried for encephalic, wherein selection shortest path is in order to avoid the influence of bifurcated center line.Meanwhile
The center line of tumor blood-vessel image is carried along the encephalic, node-by-node algorithm vessel borders carry the center of tumor blood-vessel image apart from the encephalic
The shortest distance of line carries the radius of every bit on tumor blood-vessel image center line as encephalic.
Step S103: carrying the center line and radius of tumor blood-vessel image based on the encephalic, carries out intracranial aneurysm image
Segmentation.
It is right using the treelike center line and seed point of the partial 3 d image of aforementioned acquisition using seed point coordinate as starting point
Intracranial aneurysm image carries out morphological dilations, the intracranial aneurysm image after being expanded.Take into account computational efficiency and aneurysm
Size, it is 16 times that above-mentioned preset value, which can choose, after above-mentioned partial 3 d image expansion 16 times, is obtained comprising complete entocranial artery
Then intracranial aneurysm image after the expansion of tumor image carries tumor blood-vessel image to the knot of expansion using the encephalic to be split
Fruit image is split, the intracranial aneurysm image expanded.The intracranial aneurysm image of expansion needs further progress point
It cuts.Specifically, along the encephalic carry tumor blood-vessel image center line, using encephalic carry tumor blood-vessel image radius weighted value as away from
From threshold value, the intracranial aneurysm image of above-mentioned expansion is split.In a particular embodiment, it can choose encephalic and carry tumor blood vessel
1.1 times of the radius of image as encephalic carry tumor blood-vessel image radius weighted value as distance threshold, by distance threshold range
The intracranial aneurysm image of interior generation is reset, and realizes the segmentation of aforementioned obtained intracranial aneurysm image.Then it is sat with seed point
It is designated as growth starting point, region growing is carried out to the intracranial aneurysm image after segmentation, realizes that intracranial aneurysm image and encephalic carry
The segmentation of tumor blood-vessel image obtains complete, clean intracranial aneurysm image.
Fig. 4 is the effect diagram for the intracranial aneurysm image segmentation that this specification provides.From the schematic diagram, it can see
It arrives, the accurate segmentation of aneurysm image may be implemented in the method provided using this specification.
Fig. 5 is a kind of flow chart of the dividing method for intracranial aneurysm image that this specification provides.
Step S501: carrying on tumor blood-vessel image from encephalic to be split, obtains seed point coordinate and anchor point coordinate.
Common image format of the DSA and MRA image as intracranial aneurysm, due to there are disturbing factors such as backgrounds,
In the application such as clinical teaching research, need to carry out the segmentation that encephalic carries tumor blood-vessel image first.3-D image based on DSA,
By the method for region growing, the segmentation that encephalic carries tumor blood-vessel image may be implemented；And the 3-D image based on MRA, pass through area
Between two-value method, may be implemented encephalic carry tumor blood-vessel image segmentation.
In the embodiment of this specification, the determination of seed point coordinate and anchor point coordinate may be implemented to carry tumor vessel graph
The calculating of inconocenter line and radius generates intracranial aneurysm image.Seed point coordinate is determined according to the method for abovementioned steps S102
With anchor point coordinate.
Step S502: according to seed point coordinate and anchor point coordinate, partial 3 d image is intercepted.
Using the seed point coordinate and anchor point coordinate of aforementioned acquisition, a minimum cuboid is determined.Determining minimum is long
Cube, the pixel increment for carrying out transverse direction and longitudinal direction extend, and make after extending include whole intracranial aneurysm images, after extension
Determining rectangular body region intercepts partial 3 d image.
Step S503: the treelike center line of the partial 3 d image is obtained.
Since data processing amount is little, the mode of image procossing can be taken, calculates the office intercepted in step S502
The treelike center line of portion's 3-D image.Treelike center line, that is, blood vessel center line is named since blood vessel looks like a tree
Make treelike center line.
In specific implementation process, the treelike center line of above-mentioned partial 3 d image can be by removing one from topography
A little points obtain.How Fig. 6 judges certain when obtaining the treelike center line of partial 3 d image for what this specification embodiment provided
Whether point can be deleted.Specific judgment basis is as follows: internal point cannot delete；Isolated point cannot be deleted；Straight line endpoint cannot be deleted；
If P is boundary point, after removing P, if connected component does not increase, P can be deleted.Specifically, first point cannot be deleted,
Because it is internal point；Second point cannot be deleted, because it is internal point；Third point cannot be deleted, and original can be made after deletion
Part to be connected disconnects；4th point can remove, this point is not skeleton；5th point cannot be deleted, it is straight line
Endpoint；6th point cannot be deleted, it is the endpoint of straight line.
According to above-mentioned judgment basis, make a concordance list, share 256 elements from 0 to 255, each element or
It is 0 or is 1.According to certain point (such as it is to be processed be black point) eight consecutive points the case where table look-up, if the element in table
It is 1, then it represents that the point can be deleted, and otherwise retain.
In the specific implementation process, whole image is scanned by a line a line, for each point, is calculated it and is being indexed
Index in table retains if 0, deletes the point if 1.If none point of single pass is deleted, knot is recycled
Beam, remaining point are the treelike center line of above-mentioned partial 3 d image.If be a little deleted, sweeping for a new round is carried out
It retouches, repeatedly, until there is no a little to be deleted.According to the method described above, the treelike center of the partial 3 d image is finally obtained
Line.
Step S504: center line and radius that encephalic carries tumor blood-vessel image are calculated.
The treelike center line of the partial 3 d image obtained along step S503 calculates in step S501 between two anchor points
Shortest path carries the center line of tumor blood-vessel image as encephalic, and adopting this method can be to avoid bifurcated center line to subsequent point
Cut the influence of effect.Further, the center line of tumor blood-vessel image is carried along above-mentioned encephalic, node-by-node algorithm vessel borders are apart from institute
The shortest distance that encephalic carries the center line of tumor blood-vessel image is stated, carries half of every bit on tumor blood-vessel image center line as encephalic
Diameter.
Step S505: morphological dilations generate the intracranial aneurysm image of expansion.
The purpose of morphological dilations is to obtain the image for including whole intracranial aneurysm images.When specific implementation, adopt
With the following method: using seed point coordinate as starting point, utilize the treelike center line and seed of the partial 3 d image of aforementioned acquisition
Point carries out morphological dilations to intracranial aneurysm image, the intracranial aneurysm image after being expanded.It takes into account computational efficiency and moves
Arteries and veins tumor size, it is 16 times that above-mentioned preset value, which can choose, after above-mentioned partial 3 d image expansion 16 times, is obtained comprising complete encephalic
Then intracranial aneurysm image after the expansion of aneurysm image carries tumor blood-vessel image to expansion using the encephalic to be split
Result images be split, the intracranial aneurysm image expanded.
Step S506: the intracranial aneurysm image of expansion is split.
The intracranial aneurysm image for the expansion that step S505 is obtained needs further to be partitioned into encephalic load tumor blood-vessel image
Come, leaves interested intracranial aneurysm image.Specifically, carrying the center line of tumor blood-vessel image along the encephalic, carried with encephalic
The weighted value of tumor blood-vessel image radius is split the intracranial aneurysm image of above-mentioned expansion as distance threshold, thus will
Encephalic carries tumor blood-vessel image and separates, and only leaves interested intracranial aneurysm image.Wherein, tumor blood-vessel image is carried with encephalic
1.1 times of the radius weighted values for carrying tumor blood-vessel image radius as encephalic.
Step S507: region growing, the intracranial aneurysm image divided.
The intracranial aneurysm image of above-mentioned segmentation, since there are obscure boundaries etc. to interfere, it is therefore desirable to further to segmentation
Intracranial aneurysm image handled, remove disturbing factor, to obtain clean, complete intracranial aneurysm image.Above-mentioned
The aneurysm image for the segmentation arrived is bianry image, therefore is obtained using the method for region growing using seed point coordinate as growing point
The intracranial aneurysm image that must be connected to finally obtains and divides complete, clean intracranial aneurysm image.
Fig. 7 is a kind of schematic diagram of the segmenting system for intracranial aneurysm image that this specification provides.Segmenting system tool
Body includes:
Input interface carries the input of tumor blood-vessel image for encephalic to be split；
Processing workstation carries the center line and radius of tumor blood-vessel image based on encephalic, carries out point of intracranial aneurysm image
It cuts；
Output unit exports the intracranial aneurysm image of segmentation.
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 (13)
1. a kind of dividing method of intracranial aneurysm image, which comprises the following steps:
It is carried on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image；
The treelike center line for obtaining the partial 3 d image calculates center line and radius that the encephalic carries tumor blood-vessel image；
The center line and radius of tumor blood-vessel image are carried based on the encephalic, carry out the segmentation of intracranial aneurysm image.
2. the method as described in claim 1, which is characterized in that described to be carried on tumor blood-vessel image from encephalic to be split, interception
Partial 3 d image, specifically includes:
It is carried on tumor blood-vessel image from encephalic to be split, determines seed point coordinate and anchor point coordinate；
According to seed point coordinate and anchor point coordinate, partial 3 d image is intercepted.
3. the method as described in claim 1, which is characterized in that the treelike center line for obtaining the partial 3 d image,
Center line and radius that the encephalic carries tumor blood-vessel image are calculated, is specifically included:
Using look-up table, the point in the partial 3 d image is deleted, obtain the partial 3 d image it is tree-shaped in
Heart line；
Along the treelike center line, the shortest path between described two anchor points is calculated, is carried in tumor blood-vessel image as encephalic
Heart line；
The center line of tumor blood-vessel image is carried along the encephalic, node-by-node algorithm vessel borders carry tumor blood-vessel image apart from the encephalic
The shortest distance of center line carries the radius of every bit on tumor blood-vessel image center line as encephalic.
4. the method as described in claim 1, which is characterized in that it is described based on the encephalic carry tumor blood-vessel image center line and
Radius carries out the segmentation of intracranial aneurysm image, specifically includes:
Using the treelike center line and the seed point coordinate of the partial 3 d image, morphological dilations are carried out, are then utilized
The encephalic to be split carries tumor blood-vessel image and is split to the result images of expansion, the intracranial aneurysm figure expanded
Picture；
The center line that tumor blood-vessel image is carried along the encephalic carries the weighted value of tumor blood-vessel image radius as apart from threshold using encephalic
Value, is split the intracranial aneurysm image of the expansion；
Intracranial aneurysm image after segmentation is rebuild, the intracranial aneurysm image divided.
5. method as claimed in claim 4, which is characterized in that the center line that tumor blood-vessel image is carried along the encephalic, with
Encephalic carries the weighted value of tumor blood-vessel image radius as distance threshold, is split to the intracranial aneurysm image of the expansion,
It specifically includes:
The center line that tumor blood-vessel image is carried along the encephalic is carried using 1.1 times of the radius of encephalic load tumor blood-vessel image as encephalic
The weighted value of tumor blood-vessel image radius；
Using the weighted value of encephalic load tumor blood-vessel image radius as distance threshold, the encephalic that will be generated within the scope of distance threshold
Aneurysm image is reset, and realizes the segmentation to the intracranial aneurysm image of the expansion.
6. method as claimed in claim 4, which is characterized in that the intracranial aneurysm image after described pair of segmentation is rebuild,
The intracranial aneurysm image divided, specifically includes:
The intracranial aneurysm image after segmentation is rebuild, is divided using region growing method using seed point coordinate
Intracranial aneurysm image.
7. a kind of segmenting system of intracranial aneurysm image characterized by comprising
Input interface carries the input of tumor blood-vessel image for encephalic to be split；
Processing workstation carries the center line and radius of tumor blood-vessel image based on encephalic, carries out the segmentation of intracranial aneurysm image；
Output unit exports the intracranial aneurysm image of segmentation.
8. system according to claim 7, which is characterized in that the center line and half for carrying tumor blood-vessel image based on encephalic
Diameter carries out the segmentation of intracranial aneurysm image, specifically includes:
It is carried on tumor blood-vessel image from encephalic to be split, intercepts partial 3 d image；
The treelike center line for obtaining the partial 3 d image calculates center line and radius that the encephalic carries tumor blood-vessel image；
The center line and radius of tumor blood-vessel image are carried based on the encephalic, carry out the segmentation of intracranial aneurysm image.
9. system as claimed in claim 8, which is characterized in that described to be carried on tumor blood-vessel image from encephalic to be split, interception
Partial 3 d image, specifically includes:
It is carried on tumor blood-vessel image from encephalic to be split, determines seed point coordinate and anchor point coordinate；
According to seed point coordinate and anchor point coordinate, partial 3 d image is intercepted.
10. system as claimed in claim 8, which is characterized in that the treelike center line for obtaining the partial 3 d image,
Center line and radius that the encephalic carries tumor blood-vessel image are calculated, is specifically included:
Using look-up table, the point in the partial 3 d image is deleted, obtain the partial 3 d image it is tree-shaped in
Heart line；
Along the treelike center line, the shortest path between described two anchor points is calculated, is carried in tumor blood-vessel image as encephalic
Heart line；
The center line of tumor blood-vessel image is carried along the encephalic, node-by-node algorithm vessel borders carry tumor blood-vessel image apart from the encephalic
The shortest distance of center line carries the radius of every bit on tumor blood-vessel image center line as encephalic.
11. system as claimed in claim 8, which is characterized in that the center line for carrying tumor blood-vessel image based on the encephalic
And radius, the segmentation of intracranial aneurysm image is carried out, is specifically included:
Using the treelike center line and the seed point coordinate of the partial 3 d image, morphological dilations are carried out, are then utilized
The encephalic to be split carries tumor blood-vessel image and is split to the result images of expansion, the intracranial aneurysm figure expanded
Picture；
The center line that tumor blood-vessel image is carried along the encephalic carries the weighted value of tumor blood-vessel image radius as apart from threshold using encephalic
Value, is split the intracranial aneurysm image of the expansion；
Intracranial aneurysm image after segmentation is rebuild, the intracranial aneurysm image divided.
12. system as claimed in claim 11, which is characterized in that the center line that tumor blood-vessel image is carried along the encephalic,
The weighted value for carrying tumor blood-vessel image radius using encephalic divides the intracranial aneurysm image of the expansion as distance threshold
It cuts, specifically includes:
The center line that tumor blood-vessel image is carried along the encephalic is carried using 1.1 times of the radius of encephalic load tumor blood-vessel image as encephalic
The weighted value of tumor blood-vessel image radius；
Using the weighted value of encephalic load tumor blood-vessel image radius as distance threshold, the encephalic that will be generated within the scope of distance threshold
Aneurysm image is reset, and realizes the segmentation to the intracranial aneurysm image of the expansion.
13. system as claimed in claim 11, which is characterized in that the intracranial aneurysm image after described pair of segmentation carries out weight
It builds, the intracranial aneurysm image divided specifically includes:
The intracranial aneurysm image after segmentation is rebuild using region growing method using seed point coordinate, completes encephalic
The segmentation of aneurysm image.
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