TY - GEN
T1 - Cerebral arteries extraction using level set segmentation and adaptive tracing for CT angiography
AU - Zhang, Yong
AU - Young, Geoff
AU - Zhou, Xiaobo
AU - Srinivasan, Ranga
AU - Wong, Stephen T.C.
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - We propose an approach for extracting cerebral arteries from partial Computed Tomography Angiography (CTA). The challenges of extracting cerebral arteries from CTA come from the fact that arteries are usually surrounded by bones and veins in the lower portion of a CTA volume. There exists strong intensity-value overlap between vessels and surrounding objects. Besides, it is inappropriate to assume the 2D cross sections of arteries are circle or ellipse, especially for abnormal vessels. The navigation of the arteries could change suddenly in the 3D space. In this paper, a method based on level set segmentation is proposed to target this challenging problem. For the lower portion of a CTA volume, we use geodesic active contour method to detect cross section of arteries in the 2D space. The medial axis of the artery is obtained by adaptively tracking along its navigation path. This is done by finding the minimal cross section from cutting the arteries under different angles in the 3D spherical space. This method is highly automated, with minimum user input of providing only the starting point and initial navigation direction of the arteries of interests.
AB - We propose an approach for extracting cerebral arteries from partial Computed Tomography Angiography (CTA). The challenges of extracting cerebral arteries from CTA come from the fact that arteries are usually surrounded by bones and veins in the lower portion of a CTA volume. There exists strong intensity-value overlap between vessels and surrounding objects. Besides, it is inappropriate to assume the 2D cross sections of arteries are circle or ellipse, especially for abnormal vessels. The navigation of the arteries could change suddenly in the 3D space. In this paper, a method based on level set segmentation is proposed to target this challenging problem. For the lower portion of a CTA volume, we use geodesic active contour method to detect cross section of arteries in the 2D space. The medial axis of the artery is obtained by adaptively tracking along its navigation path. This is done by finding the minimal cross section from cutting the arteries under different angles in the 3D spherical space. This method is highly automated, with minimum user input of providing only the starting point and initial navigation direction of the arteries of interests.
KW - Computed tomography angiography (CTA)
KW - Geodesic active contour
KW - Vessel tracking
UR - http://www.scopus.com/inward/record.url?scp=71449115979&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71449115979&partnerID=8YFLogxK
U2 - 10.1063/1.2816644
DO - 10.1063/1.2816644
M3 - Conference contribution
AN - SCOPUS:71449115979
SN - 9780735404663
T3 - AIP Conference Proceedings
SP - 57
EP - 65
BT - Computational Models For Life Sciences (CMLS '07) - 2007 International Symposium
T2 - 2007 International Symposium on Computational Models for Life Sciences, CMLS '07
Y2 - 17 December 2007 through 19 December 2007
ER -