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Abstract:
Coronary artery centerline play an important role in diagnosing cardiovascular disease, coronary artery registration, fusion, biplane reconstruction and so on. It is still very difficult to extract centerline from coronary angiographic images with noise and uneven distribution agents. An centerline extraction algorithm based on tracking and boundary information of coronary artery was proposed in this paper, tracking was based on Hessian matrix's eigenvalues and eigenvectors and the boundary information was obtained from narrow band level set method. The bifurcation points and endpoints of centerline which obtained from centerline extraction algorithm were used to segment coronary artery tree. Simulation angiography images and clinical images that contain noise and uneven contrast media were used to evaluate the performance of proposed algorithm. The experimental results demonstrated that coronary artery centerlines were extracted effectively and completely and coronary artery trees were divided into several segments by using proposed algorithm. This algorithm can work normally even the images contains noise and uneven contrast media.
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JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS
ISSN: 2156-7018
Year: 2018
Issue: 6
Volume: 8
Page: 1226-1232
ESI Discipline: CLINICAL MEDICINE;
ESI HC Threshold:167
JCR Journal Grade:4
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 8
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