Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree
2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007: 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I / [ed] Nicholas Ayache, Sébastien Ourselin, Anthony Maeder, Springer Berlin/Heidelberg, 2007, Vol. 4791, 311-318 p.Conference paper (Refereed)
We propose a new segmentation algorithm based on competing fuzzy connectedness theory, which is then used for visualizing coronary arteries in 3D CT angiography (CTA) images. The major difference compared to other fuzzy connectedness algorithms is that an additional data structure, the connectedness tree, is constructed at the same time as the seeds propagate. In preliminary evaluations, accurate result have been achieved with very limited user interaction. In addition to improving computational speed and segmentation results, the fuzzy connectedness tree algorithm also includes automated extraction of the vessel centerlines, which is a promising approach for creating curved plane reformat (CPR) images along arteries’ long axes.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007. Vol. 4791, 311-318 p.
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 4791
segmentation - fuzzy connectedness tree - centerline extraction - skeletonization - coronary artery - CT angiography
Radiology, Nuclear Medicine and Medical Imaging Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-17816DOI: 10.1007/978-3-540-75757-3_38ISI: 000250916000038ISBN: 978-3-540-75756-6 (print)OAI: oai:DiVA.org:liu-17816DiVA: diva2:212251
10th International Conference on Medical Image Computing and Computer-Assisted Intervention, Brisbane, Australia, October 29 - November 2, 2007
The original publication is available at www.springerlink.com: Chunliang Wang and Örjan Smedby, Coronary Artery Segmentation and Skeletonization Based on Competing Fuzzy Connectedness Tree, 2007, Medical Image Computing and Computer-Assisted Intervention, (4791), 311-318. http://dx.doi.org/10.1007/978-3-540-75757-3_38 Copyright: Springer-verlag http://www.springerlink.com/2009-04-212009-04-212014-09-24Bibliographically approved