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

Sylvain Faisan (1) , Nicolas Passat (1) , Vincent Noblet (1) , Renée Chabrier (2) , Christophe Meyer (3)

1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LINC - Laboratoire d'Imagerie et de Neurosciences Cognitives
3 Hôpitaux Universitaires de Besançon

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.

Domaines: Traitement des images [eess.IV]; Imagerie médicale

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⟩