Vessel segmentation for ablation treatment planning and simulation
Alhonnoro T, Pollari M, Lilja M, Flanagan R, Kainz B, Muehl J, Mayrhauser U, Portugaller H, Stiegler P, Tscheliessnigg K (2010)
Publication Type: Conference contribution
Publication year: 2010
Journal
Book Volume: 6361 LNCS
Pages Range: 45-52
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: CHN
ISBN: 3642157041
DOI: 10.1007/978-3-642-15705-9_6
Abstract
In this paper, a novel segmentation method for liver vasculature is presented, intended for numerical simulation of radio frequency ablation (RFA). The developed method is a semiautomatic hybrid based on multi-scale vessel enhancement combined with ridge-oriented region growing and skeleton-based postprocessing. In addition, an interactive tool for segmentation refinement was developed. Four instances of three-phase contrast enhanced computed tomography (CT) images of porcine liver were used in the evaluation. The results showed improved accuracy over common approaches and illustrated the method's suitability for simulation purposes. © 2010 Springer-Verlag.
Authors with CRIS profile
Involved external institutions
Aalto University Espoo
Finland (FI)
NUMA Engineering Services Ltd
Ireland (IE)
Technische Universität Graz
Austria (AT)
Medizinische Universität Graz
Austria (AT)
Finland (FI)
NUMA Engineering Services Ltd
Ireland (IE)
Technische Universität Graz
Austria (AT)
Medizinische Universität Graz
Austria (AT)
How to cite
APA:
Alhonnoro, T., Pollari, M., Lilja, M., Flanagan, R., Kainz, B., Muehl, J.,... Tscheliessnigg, K. (2010). Vessel segmentation for ablation treatment planning and simulation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 45-52). CHN.
MLA:
Alhonnoro, Tuomas, et al. "Vessel segmentation for ablation treatment planning and simulation." Proceedings of the 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, CHN 2010. 45-52.
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