CN104166979A - Blood vessel extracting method - Google Patents
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Abstract
The invention provides a blood vessel extracting method comprising the steps of providing head and neck CT angiography data, dividing the head and neck CT angiography data into a plurality of parts, and adopting corresponding vessel extraction algorithms to perform blood vessel extraction on the plurality of parts. Considering that vessels of different parts of the head and neck region differ greatly in morphology, the head and neck region is divided into four blocks in the method, and extraction of the blood vessels of the head and neck region is realized by combining a region growing algorithm, a level set algorithm and a dynamic tracking algorithm. The method has good robustness, is high in blood vessel extraction speed, and is applicable to data of different manufacturers.
Description
Technical field
The present invention relates to a kind of disposal route of medical science tomoscan image, relate in particular to a kind of vessel extraction method.
Background technology
Angiography (Computed Tomography Ang i ography is called for short CTA) is one of important method of current diagnosis vascular diseases, is mainly used in clinically the multiple vascular diseases of diagnosis and treatment, as aneurysm, hemadostewnosis, angiosteosis etc.But because the CT value of its hetero-organizations such as the blood vessel in CTA image and bone is overlapping, so blood vessel is extracted from its hetero-organization, be the committed step in Angiography.
Americana 1:P.T.Vieco, W.P.Shuman, G.F.Alsofrom, the scissors for vessels image method that C.E.Gross.Detection of circle of Willis aneurysms in patients with acute subarachnoid hemorrhage:a comparison of CT angiography and digital subtraction angiography.AJR vol.165no.2425-430 (1995) provides, twice of client need same position scanning (being respectively not injection of contrast medium scanning and injection of contrast medium scanning), obtain non-CTA image and CTA image.Because the blood vessel CT value in non-CTA image is lower than CTA image medium vessels CT value, two kinds of scan images are carried out after registration, then subtract each other just can be by vessel extraction out.But the method need to scan twice to patient, more consuming time, to patient, bring more scanning radiation amount simultaneously.
Americana 2:O livier Cuisenairea, Sunny Virmanib, MarkE.Olszewskib, Roberto Ardona.Fully automated segmentation of carotid and vertebral arteries from contrast enhanced CTA.Proc.of SPIE Vol.6914,69143R, (2008) provide a kind of method based on model, first by CTA image and existing vascular pattern registration, obtain the starting point of different blood vessel, then by algorithm, connect starting point, obtain the center line of blood vessel.Finally, take center line as initial, by simple grid, expand outwardly, extract blood vessel.The method effect is better, but calculating is very complicated, and extraction rate is extremely slow, inapplicable practical clinical.
Americana 3:Hackjoon Shim, II Dong Yun, Kyoung Mu Lee, and Sang Uk Lee.Partition-Based Extraction of Cerebral Arteries from CT Angiography with Emphas is on Adaptive Tracking.IPMI, LNCS3565, pp.357-368 (2005) has proposed a kind of semi-automatic incidence vessel extraction algorithm.First this algorithm is divided into incidence volume data a He Tou bottom, top.For a top, adopt region growing algorithm to extract blood vessel.For a bottom, manually determine after blood vessel Seed Points, adopt the dynamic track method based on Ray-Casting to extract blood vessel.This algorithm poor robustness, need to regulate parameter could realize the vessel extraction of different pieces of information, and the while cannot the large vertebral artery of the Extraction parts anglec of rotation.
Further, incidence vessel extraction is the most important also challenging task of tool in angiogram (CTA) technology.Incidence artery mainly comprises arteria carotis communis (CCA), internal carotid (ICA), external carotid artery (ECA), vertebral artery (VA), basal arteries (BA) etc.Arteria carotis communis bifurcated is internal carotid and external carotid artery, and wherein internal carotid, through skull, is given front portion and the middle part blood supply of brain; External carotid artery is tooth and face nerve blood supply.Left and right vertebral artery is walked in a section vertebra, is finally merged into basal arteries, through occipital bone, is the rear portion blood supply of brain.Clinically, the blood vessel being partitioned into can be used to the various vascular diseases of quantitative diagnosis, and as arteria carotis communis and internal carotid easily start pulse atherosclerosis, vertebral artery is easily narrow etc., and these pathologies are also the main causes of large headstroke.In CTA incidence image, above-mentioned blood vessel and bone are spatially close to very much, and CT value overlaps.General algorithm is as region growing, and level set etc. are easy to obscure blood vessel and bone, causes blood vessel segmentation failure.
Summary of the invention
The problem that the present invention solves is to provide a kind of vessel extraction method, the problem of cutting apart in order to solve incidence vessel extraction.
In order to address the above problem, the invention provides a kind of vessel extraction method, comprise incidence CT radiography data are provided, and described incidence CT radiography data are divided into some portions, to described some, adopt respectively corresponding vessel extraction algorithm to carry out vessel extraction.
Optionally, described some portions comprise: a top, centriciput, a bottom and chest.
Optionally, the image on described top is carried out to assignment, according to described assignment, determine blood vessel Seed Points, and carry out region growing based on described Seed Points, to carry out the extraction of described top blood vessel.
Optionally, described assignment comprises: extract bone and described bone is expanded, and to described bone and dilation assignment.
Optionally, also comprise: the vessel extraction to described centriciput, a bottom and chest comprises, according to entropy location and blood vessel, strengthens the Seed Points that extracts each artery in described some layers.
Optionally, to described centriciput blood vessel, adopt entropy localization method to determine the above image layer of vertebral artery point, by blood vessel Enhancement Method, find basal arteries Seed Points; The Level Set Method of differentiating based on radius is extracted described basal arteries and the vertebral artery that is positioned at this portion.
Optionally, described centriciput blood vessel is also comprised: first survey tracheae and throat connecting place image layer, in the image range of image layer that includes described connecting place, adopt blood vessel Enhancement Method to determine described internal carotid Seed Points, and the dynamic tracing method of differentiating based on level set is extracted the described internal carotid that is positioned at this portion.
Optionally, for described bottom blood vessel, comprise: adopt entropy location to find neck entropy smallest tier, and find arteria carotis communis Seed Points near described entropy smallest tier, finally the level set based on radius judgement extracts arteria carotis communis, external carotid artery and the internal carotid that is positioned at this portion.
Optionally, for described bottom blood vessel, also comprise: to described vertebrarterial extraction, first detect vertebra, adopting oval detection method to find comprises vertebra but does not comprise neural spine and the image layer of the centrum of transverse process, in the image range of the image layer that comprises described correspondence, adopt blood vessel Enhancement Method to find vertebral artery Seed Points, the dynamic tracing method of finally differentiating based on level set is extracted the vertebral artery that is positioned at this portion.
Optionally, to described chest blood vessel, first according to entropy location, determine sustainer place image layer, within comprising its image range, adopt blood vessel Enhancement Method to extract aorta ascendens or descending aorta center, and as sustainer Seed Points, the region growing method of finally differentiating based on radius gradient is extracted the chest blood vessel that is positioned at this portion.
Optionally, by the method for entropy and image registration, described incidence is carried out to layering.
The present invention has the following advantages and beneficial effect:
The present invention is directed to the large feature of each position vascular morphology difference of incidence, first the method is divided into incidence 4, calmodulin binding domain CaM growth algorithm, level set algorithm and dynamic track method are realized incidence vessel extraction, the method robustness is good, vessel extraction speed is fast, is applicable to the data of different manufacturers.
Accompanying drawing explanation
Fig. 1 is the division schematic diagram of some portions of the vessel extraction method of one embodiment of the invention;
Fig. 2 is the schematic flow sheet of the vessel extraction method of one embodiment of the invention;
The angiographic image of Fig. 3 for starting scanning and start scanning from neck from chest belly respectively.
Embodiment
A lot of details have been set forth in the following description so that fully understand the present invention.But the present invention can implement to be much different from alternate manner described here, and those skilled in the art can do similar popularization without prejudice to intension of the present invention in the situation that, so the present invention is not subject to the restriction of following public concrete enforcement.
Secondly, the present invention utilizes schematic diagram to be described in detail, and when the embodiment of the present invention is described in detail in detail, for ease of explanation, described schematic diagram is example, and it should not limit the scope of protection of the invention at this.
The problem of cutting apart in order to solve incidence vessel extraction, the invention provides a kind of vessel extraction method, comprise incidence CT radiography data are provided, and described incidence CT radiography data are divided into some portions, to described some, adopt respectively corresponding vessel extraction algorithm to carry out vessel extraction.Described some portions comprise: a top, centriciput, a bottom and chest.Particularly, can to described incidence, carry out layering by the method for entropy and image registration.
Wherein, the image on described top is carried out to assignment, according to described assignment, determine blood vessel Seed Points, and carry out region growing based on described Seed Points, to carry out the extraction of described top blood vessel; Vessel extraction to described centriciput, a bottom and chest comprises, according to entropy location and blood vessel, strengthens the Seed Points that extracts each artery in described some layers.
Further, above-mentioned assignment comprises: extract bone and described bone is expanded, and to described bone and dilation assignment.
The vessel extraction of concrete different parts comprises: to described centriciput blood vessel, adopt entropy localization method to determine the above image layer of vertebral artery point, by blood vessel Enhancement Method, find basal arteries Seed Points; The Level Set Method of differentiating based on radius is extracted described basal arteries and the vertebral artery that is positioned at this portion; Also comprise and first survey tracheae and throat connecting place image layer, in the image range of image layer that includes described connecting place, adopt blood vessel Enhancement Method to determine described internal carotid Seed Points, and the dynamic tracing method of differentiating based on level set is extracted the described internal carotid that is positioned at this portion.
For described bottom blood vessel, comprise: adopt entropy location to find neck entropy smallest tier, and find Carotid Seed Points near described entropy smallest tier, finally the level set based on radius judgement extracts arteria carotis communis, external carotid artery and the internal carotid that is positioned at this portion.Also comprise: to described vertebrarterial extraction, first detect vertebra, adopting oval detection method to find comprises vertebra but does not comprise neural spine and the image layer of the centrum of transverse process, in the image range of the image layer that comprises described correspondence, adopt blood vessel Enhancement Method to find vertebral artery Seed Points, the dynamic tracing method of finally differentiating based on level set is extracted the vertebral artery that is positioned at this portion.
Finally, to described chest blood vessel, first according to entropy location, determine sustainer place image layer, within comprising its image range, adopt blood vessel Enhancement Method to extract aorta ascendens or descending aorta center, and as sustainer Seed Points, the region growing method of finally differentiating based on radius gradient is extracted the chest blood vessel that is positioned at this portion.
Below in conjunction with accompanying drawing, embodiments of the invention are elaborated.
If Fig. 1 is the division schematic diagram of some portions of the vessel extraction method of one embodiment of the invention.Incidence CT radiography data are divided into 4 parts automatically, a top, centriciput, a bottom and chest, adopt different vessel extraction algorithms to different parts afterwards, finally merges the blood vessel at each position, realizes the complete extraction of blood vessel.
Each position vascular morphology difference of incidence is large, and as a top rich blood vessel, blood vessel and skull are relatively far apart; The internal carotid of centriciput (ICA) is closely connected to realize with vertebral artery (VA) and skull wears cranium; The vertebral artery (VA) of bottom is walked in vertebra, is connected tight etc. with vertebra.Single algorithm is difficult to the vessel extraction of applicable above-mentioned these situations, need adopt specific algorithm to realize vessel extraction to different parts.
Fig. 2 is the schematic flow sheet of the vessel extraction method of one embodiment of the invention, and method step is as follows:
The angiogram of read head (CTA) data; By the method for entropy and registration, head ct angiography (CTA) data are carried out to layering, be divided into a top, centriciput, a bottom and chest.
Particularly, correct top blood vessel: first extract bone, and bone is expanded, then by bone in angiogram (CTA) data and dilation tax 0 or negative value; Then according to threshold value, look for blood vessel Seed Points, on the basis of these Seed Points, carry out region growing and extract blood vessel.
To centriciput blood vessel: mainly extract basal arteries (BA), vertebral artery (VA), internal carotid (ICA).For the extraction of basal arteries (BA) and vertebral artery (VA), first adopt entropy localization method to find the above image layer of vertebral artery (VA) point, by blood vessel Enhancement Method, find basal arteries (BA) Seed Points.Then use the Level Set Method of differentiating based on radius to extract and be positioned at the basal arteries (BA) of this portion and the vertebral artery (VA) of this part head; Extraction for internal carotid (ICA), first survey tracheae and throat connecting place image layer, near this image layer in the certain angle of tracheae left and right, adopt blood vessel Enhancement Method to find internal carotid (ICA) Seed Points, then use the dynamic tracing method of differentiating based on level set to extract the internal carotid (ICA) that is positioned at this portion.
Correct bottom blood vessel: the Seed Points that first extracts respectively arteria carotis communis (CCA) and vertebral artery (VA) according to entropy location and blood vessel Enhancement Method.
Extraction for arteria carotis communis (CCA), first adopt entropy localization method to find neck entropy smallest tier, near this image layer, by blood vessel Enhancement Method, find the Seed Points of arteria carotis communis (CCA), then use the Level Set Method of differentiating based on radius to extract and be positioned at the arteria carotis communis (CCA) of this portion and the external carotid artery (ECA) of this part head and internal carotid (ICA).
Extraction for vertebral artery (VA), first detect vertebra, adopt oval detection method to find the centrum that only comprises vertebra, and without the image layer of neural spine and transverse process, near this image layer in the certain angle of vertebra both sides, adopt blood vessel Enhancement Method to find vertebral artery (VA) Seed Points, then use the dynamic tracing method of differentiating based on level set to extract the vertebral artery (VA) that is positioned at this portion.
To chest blood vessel: first determine sustainer place image layer according to entropy location, near this image layer, adopt blood vessel Enhancement Method extraction aorta ascendens or descending aorta center as sustainer Seed Points, then use the region growing method of differentiating based on radius gradient to extract the chest blood vessel that is positioned at this portion.
The blood vessel being extracted separately by a top, centriciput, a bottom and chest is merged, obtain final head blood vessel result.
Fig. 3 is left for start angiogram (CTA) image of scanning from chest belly, and Fig. 3 is right for start angiogram (CTA) image of scanning from neck.For head ct angiography (CTA) data that there is no chest, as shown in Fig. 3 right side, without the flow process that is labeled as 100 parts in Fig. 2 process flow diagram.Arteria carotis communis (CCA) and chest blood vessel are not extracted, because these type of data are without chest, and arteria carotis communis (CCA) only has fraction.
A kind of full-automatic incidence pipe extracting method is proposed herein.For the large feature of each position vascular morphology difference of incidence, first the method is divided into 4 automatically by incidence, calmodulin binding domain CaM growth algorithm, level set algorithm and dynamic track method are realized incidence vessel extraction, the method robustness is good, vessel extraction speed is fast, is applicable to the data of different manufacturers.
Although the present invention with preferred embodiment openly as above; but it is not for limiting the present invention; any those skilled in the art without departing from the spirit and scope of the present invention; can utilize method and the technology contents of above-mentioned announcement to make possible change and modification to technical solution of the present invention; therefore; every content that does not depart from technical solution of the present invention; any simple modification, equivalent variations and the modification above embodiment done according to technical spirit of the present invention, all belong to the protection domain of technical solution of the present invention.
Claims (11)
1. a vessel extraction method, is characterized in that, comprises incidence CT radiography data are provided, and described incidence CT radiography data are divided into some portions, to described some, adopts respectively corresponding vessel extraction algorithm to carry out vessel extraction.
2. vessel extraction method as claimed in claim 1, is characterized in that, described some portions comprise: a top, centriciput, a bottom and chest.
3. vessel extraction method as claimed in claim 2, is characterized in that, the image on described top is carried out to assignment, according to described assignment, determines blood vessel Seed Points, and carries out region growing based on described Seed Points, to carry out the extraction of described top blood vessel.
4. vessel extraction method as claimed in claim 3, is characterized in that, described assignment comprises: extract bone and described bone is expanded, and to described bone and dilation assignment.
5. vessel extraction method as claimed in claim 2, is characterized in that, also comprises: the vessel extraction to described centriciput, a bottom and chest comprises, according to entropy location and blood vessel, strengthens the Seed Points that extracts each artery in described some layers.
6. vessel extraction method as claimed in claim 5, is characterized in that, to described centriciput blood vessel, adopts entropy localization method to determine the above image layer of vertebral artery point, by blood vessel Enhancement Method, finds basal arteries Seed Points; The Level Set Method of differentiating based on radius is extracted basal arteries and the vertebral artery that is positioned at this portion.
7. vessel extraction method as claimed in claim 6, it is characterized in that, described centriciput blood vessel is also comprised: first survey tracheae and throat connecting place image layer, in the image range of image layer that includes described connecting place, adopt blood vessel Enhancement Method to determine described internal carotid Seed Points, and the dynamic tracing method of differentiating based on level set is extracted the described internal carotid that is positioned at this portion.
8. vessel extraction method as claimed in claim 5, it is characterized in that, for described bottom blood vessel, comprise: adopt entropy location to find neck entropy smallest tier, and find arteria carotis communis Seed Points near described entropy smallest tier, finally the level set based on radius judgement extracts arteria carotis communis, external carotid artery and the internal carotid that is positioned at this portion.
9. vessel extraction method as claimed in claim 8, it is characterized in that, for described bottom blood vessel, also comprise: to described vertebrarterial extraction, first detect vertebra, adopt oval detection method to find and comprise vertebra but do not comprise neural spine and the image layer of the centrum of transverse process, in the image range of the image layer that comprises described correspondence, adopt blood vessel Enhancement Method to find vertebral artery Seed Points, the dynamic tracing method of finally differentiating based on level set is extracted the vertebral artery that is positioned at this portion.
10. vessel extraction method as claimed in claim 5, it is characterized in that, to described chest blood vessel, first according to entropy location, determine sustainer place image layer, within comprising its image range, adopt blood vessel Enhancement Method to extract aorta ascendens or descending aorta center, and as sustainer Seed Points, the region growing method of finally differentiating based on radius gradient is extracted chest blood vessel.
11. vessel extraction methods as claimed in claim 1, is characterized in that, by the method for entropy and image registration, described incidence are carried out to layering.
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| US11344273B2 (en) | 2016-06-30 | 2022-05-31 | Shanghai United Imaging Healthcare Co., Ltd. | Methods and systems for extracting blood vessel |
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| US10861158B2 (en) | 2017-01-23 | 2020-12-08 | Shanghai United Imaging Healthcare Co., Ltd. | Method and system for acquiring status of strain and stress of a vessel wall |
| US11468570B2 (en) | 2017-01-23 | 2022-10-11 | Shanghai United Imaging Healthcare Co., Ltd. | Method and system for acquiring status of strain and stress of a vessel wall |
| CN107025646A (en) * | 2017-03-03 | 2017-08-08 | 沈阳东软医疗系统有限公司 | A kind of lower limb vascular extracting method and device |
| CN107025646B (en) * | 2017-03-03 | 2021-03-05 | 东软医疗系统股份有限公司 | Lower limb blood vessel extraction method and device |
| CN109410191A (en) * | 2018-10-18 | 2019-03-01 | 中南大学 | Optical fundus blood vessel localization method and its anaemia screening method based on OCT image |
| CN109410191B (en) * | 2018-10-18 | 2022-03-25 | 中南大学 | OCT (optical coherence tomography) image-based fundus blood vessel positioning method and anemia screening method thereof |
| CN109712163A (en) * | 2018-12-05 | 2019-05-03 | 上海联影医疗科技有限公司 | Coronary artery extracting method, device, image processing workstations and readable storage medium storing program for executing |
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