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.
Complete list of metadatas

https://hal.univ-reims.fr/hal-01695012
Contributor : Nicolas Passat <>
Submitted on : Monday, February 26, 2018 - 1:07:41 PM
Last modification on : Thursday, July 19, 2018 - 3:34:01 PM
Long-term archiving on : Monday, May 28, 2018 - 4:40:09 PM

File

Faisan_MICCAI_2008.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

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⟩

Share

Metrics

Record views

106

Files downloads

92