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Conference papers

Topology preserving warping of binary images: Application to atlas-based skull segmentation

Abstract : Lots of works have been recently carried out in the field of non-rigid registration to ensure the estimation of one-to-one mappings. However, warping a binary image with such transformations may alter its discrete topological properties if common resampling strategies are considered. This paper proposes an original method for warping a binary image according to some continuous and bijective mapping, while preserving its discrete topological properties. Results obtained in the context of atlas-based segmentation highlight the interest of the approach. Indeed, the method has been successfully applied to the segmentation of skull structures from a database of 15 CT-scans, providing both geometrically and topologically satisfactory results.
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Contributor : Nicolas Passat Connect in order to contact the contributor
Submitted on : Monday, February 26, 2018 - 1:07:41 PM
Last modification on : Tuesday, May 24, 2022 - 9:56:02 AM
Long-term archiving on: : Monday, May 28, 2018 - 4:40:09 PM


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Sylvain Faisan, Nicolas Passat, Vincent Noblet, Renée Chabrier, Christophe Meyer. Topology preserving warping of binary images: Application to atlas-based skull segmentation. Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2008, New York, United States. pp.211-218, ⟨10.1007/978-3-540-85988-8_26⟩. ⟨hal-01695012⟩



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