A Semi-Automatic Coronary Artery Segmentation Framework Using Mechanical Simulation.
CVD (cardiovascular disease) is one of the biggest threats to human beings nowadays. An early and quantitative diagnosis of CVD is important in extending lifespan and improving people's life quality. Coronary artery stenosis can prevent CVD. To diagnose the degree of stenosis, the inner diameter of...
| Publicado en: | Journal of Medical Systems Vol. 39; no. 10; pp. 1 - 8 |
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| Autores principales: | , , , , , |
| Formato: | diagnostic images equations & formulas pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925167&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925167 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Oct2015 vid: 39 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925167 115925167 115925167 10.1007/s10916-015-0329-9 115925167 ppf: 1 ppct: 7 formats: fmt: @attributes: type: P tig: atl: A Semi-Automatic Coronary Artery Segmentation Framework Using Mechanical Simulation. aug: au: Cai, Ken Yang, Rongqian Li, Lihua Ou, Shanxing Chen, Yuke Dou, Jianhong affil: Department of Biomedical Engineering, South China University of Technology, HEMC, Guangzhou 510006 China sug: subj: Coronary Vessels Radiography Simulations Automation Coronary Stenosis Diagnosis Tomography, X-Ray Computed Image Processing, Computer Assisted Weights and Measures Algorithms Cardiovascular Diseases Diagnosis Funding Source ab: CVD (cardiovascular disease) is one of the biggest threats to human beings nowadays. An early and quantitative diagnosis of CVD is important in extending lifespan and improving people's life quality. Coronary artery stenosis can prevent CVD. To diagnose the degree of stenosis, the inner diameter of coronary artery needs to be measured. To achieve such measurement, the coronary artery is segmented by using a method that is based on morphology and the continuity between computed tomography image slices. A centerline extraction method based on mechanical simulation is proposed. This centerline extraction method can figure out a basic framework of the coronary artery by simulating pixel dots of the artery image into mass points. Such mass points have tensile forces, with which the outer pixel dots can be drawn to the center. Subsequently, the centerline of the coronary artery can be outlined by using the local line-fitting method. Finally, the nearest point method is adopted to measure the inner diameter. Experimental results showed that the methods proposed in this paper can precisely extract the centerline of the coronary artery and can accurately measure its inner diameter, thereby providing a basis for quantitative diagnosis of coronary artery stenosis. pubtype: Academic Journal doctype: diagnostic images equations & formulas pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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