Filling large discontinuities in 3D vascular networks using skeleton- and intensity-based information
Bates R, Risser L, Irving B, Papiez BW, Kannan P, Kersemans V, Schnabel JA (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9351
Pages Range: 157-164
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Munich, DEU
ISBN: 9783319245737
DOI: 10.1007/978-3-319-24574-4_19
Abstract
Segmentation of vasculature is a common task in many areas of medical imaging, but complex morphology and weak signal often lead to incomplete segmentations. In this paper, we present a new gap filling strategy for 3D vascular networks. The novelty of our approach is to combine both skeleton- and intensity-based information to fill large discontinuities. Our approach also does not make any hypothesis on the network topology, which is particularly important for tumour vasculature due to the chaotic arrangement of vessels within tumours. Synthetic results show that using intensity-based information, in addition to skeleton-based information, can make the detection of large discontinuities more robust. Our strategy is also shown to outperform a classic gap filling strategy on 3D Micro-CT images of preclinical tumour models.
Involved external institutions
University of Oxford
United Kingdom (GB)
National Center for Scientific Research / Centre national de la recherche scientifique (CNRS)
France (FR)
United Kingdom (GB)
National Center for Scientific Research / Centre national de la recherche scientifique (CNRS)
France (FR)
How to cite
APA:
Bates, R., Risser, L., Irving, B., Papiez, B.W., Kannan, P., Kersemans, V., & Schnabel, J.A. (2015). Filling large discontinuities in 3D vascular networks using skeleton- and intensity-based information. In Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 157-164). Munich, DEU: Springer Verlag.
MLA:
Bates, Russell, et al. "Filling large discontinuities in 3D vascular networks using skeleton- and intensity-based information." Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, Munich, DEU Ed. Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, William M. Wells, Springer Verlag, 2015. 157-164.
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