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Proceedings Paper

Automated registration of coronary arterial trees from multiple phases in coronary CT angiography (cCTA)
Author(s): Lubomir Hadjiiski; Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Prachi Agarwal; Jean Kuriakose; Smita Patel; Jun Wei; Ella Kazerooni
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Paper Abstract

We are developing an automated registration method for coronary arterial trees from multiple-phase cCTA to build a best-quality tree to facilitate detection of stenotic plaques. Cubic B-spline with fast localized optimization (CBSO) is designed to register the initially segmented left and right coronary arterial trees (LCA or RCA) separately in adjacent phase pairs where displacements are small. First, the corresponding trees in phase 1 and 2 are registered. The phase 3 tree is then registered to the combined tree. Similarly the trees in phases 4, 5, and 6 are registered. An affine transform with quadratic terms and nonlinear simplex optimization (AQSO) is designed to register the trees between phases with large displacements, namely, registering the combined tree from phases 1, 2, and 3 to that from phases 4, 5, and 6. Finally, CBSO is again applied to the AQSO registered volumes for final refinement. The costs determined by the distances between the vessel centerlines, bifurcation points and voxels of the trees are minimized to guide both CBSO and AQSO registration. The registration performance was evaluated on 22 LCA and 22 RCA trees on 22 CTA scans with 6 phases from 22 patients. The average distance between the centerlines of the registered trees was used as a registration quality index. The average distances for LCA and RCA registration for 6 phases and 22 patients were 1.49 and 1.43 pixels, respectively. This study demonstrates the feasibility of using automated method for registration of coronary arterial trees from multiple cCTA phases.

Paper Details

Date Published: 29 March 2013
PDF: 5 pages
Proc. SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis, 86703M (29 March 2013); doi: 10.1117/12.2008058
Show Author Affiliations
Lubomir Hadjiiski, Univ. of Michigan Health System (United States)
Chuan Zhou, Univ. of Michigan Health System (United States)
Heang-Ping Chan, Univ. of Michigan Health System (United States)
Aamer Chughtai, Univ. of Michigan Health System (United States)
Prachi Agarwal, Univ. of Michigan Health System (United States)
Jean Kuriakose, Univ. of Michigan Health System (United States)
Smita Patel, Univ. of Michigan Health System (United States)
Jun Wei, Univ. of Michigan Health System (United States)
Ella Kazerooni, Univ. of Michigan Health System (United States)


Published in SPIE Proceedings Vol. 8670:
Medical Imaging 2013: Computer-Aided Diagnosis
Carol L. Novak; Stephen Aylward, Editor(s)

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