TY - GEN
T1 - Coronary artery segmentation using geometric moments based tracking and snake-driven refinement
AU - Chen, Kun
AU - Zhang, Yong
AU - Pohl, Kilian
AU - Syeda-Mahmood, Tanveer
AU - Song, Zhihuan
AU - Wong, Stephen T C
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Automatic or semi-automatic segmentation and tracking of artery trees from computed tomography angiography (CTA) is an important step to improve the diagnosis and treatment of artery diseases, but it still remains a significant challenging problem. In this paper, we present an artery extraction method to address the challenge. The proposed method consists of two steps: (1) a geometric moments based tracking to secure a rough centerline, and (2) a fully automatic generalized cylinder structure-based snake method to refine the centerlines and estimate the radii of the arteries. In this method, a new line direction based on first and second order geometric moments is adopted while both gradient and intensity information are used in the snake model to improve the accuracy. The approach has been evaluated on synthetic images as well as 8 clinical coronary CTA images with 32 coronary arteries. Our method achieves 94.7% overlap tracking ability within an average distance inside the vessel of 0.36mm.
AB - Automatic or semi-automatic segmentation and tracking of artery trees from computed tomography angiography (CTA) is an important step to improve the diagnosis and treatment of artery diseases, but it still remains a significant challenging problem. In this paper, we present an artery extraction method to address the challenge. The proposed method consists of two steps: (1) a geometric moments based tracking to secure a rough centerline, and (2) a fully automatic generalized cylinder structure-based snake method to refine the centerlines and estimate the radii of the arteries. In this method, a new line direction based on first and second order geometric moments is adopted while both gradient and intensity information are used in the snake model to improve the accuracy. The approach has been evaluated on synthetic images as well as 8 clinical coronary CTA images with 32 coronary arteries. Our method achieves 94.7% overlap tracking ability within an average distance inside the vessel of 0.36mm.
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U2 - 10.1109/IEMBS.2010.5627192
DO - 10.1109/IEMBS.2010.5627192
M3 - Conference contribution
C2 - 21096589
AN - SCOPUS:78650817683
SN - 9781424441235
T3 - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
SP - 3133
EP - 3137
BT - 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
T2 - 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Y2 - 31 August 2010 through 4 September 2010
ER -