Segmentation of 3D cellular networks from SR-micro-CT images

Alexandra Pacureanu (1, 2, 3) , Jerome Rollet (1) , Chantal Revol-Muller (4, 1) , Vasile Buzuloiu (5, 1) , Max Langer (3, 1) , Françoise Peyrin (6, 3, 1)

1 CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé
2 Centre for image analysis and Science for Life Laboratory
3 ESRF - European Synchrotron Radiation Facility
4 INSA - Institut National des Sciences Appliquées
5 LAPI - Laboratorul de Analiza si Prelucrarea Imaginilor [Bucarest]
6 Imagerie Tomographique et Radiothérapie

Bone fragility involved in diseases such as osteoporosis implicates many mechanisms at the cellular level. It was recently shown that the lacunar-canalicular network interconnecting osteocytes has a major role in mechanosensitivity. So far, this system has only been studied from 2D microscopic images. In a previous work, we demonstrated the feasibility of synchrotron radiation micro-CT with a voxel size of 0.28μm, to image the lacunar-canalicular porosity in 3D. Nevertheless, the segmentation of this dense network of slender channels with average diameters of ~300-600 nanometers, at the limit of the spatial resolution, is difficult. In this work we propose a level set based method to automatically segment this complex system. To this aim, we designed an automatic initialization process and we apply a post-processing filter. Quantitative results on a ground truth prepared image are presented. On real data sets, expert evaluation showed good results.

Mots clés: level sets; bone; 3D image segmentation; lacunar-canalicular network; X-ray -μCT

Domaines: Imagerie

Alexandra Pacureanu, Jerome Rollet, Chantal Revol-Muller, Vasile Buzuloiu, Max Langer, et al.. Segmentation of 3D cellular networks from SR-micro-CT images. 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Mar 2011, Chicago, United States. pp.1970-1973, ⟨10.1109/ISBI.2011.5872796⟩. ⟨hal-01825257⟩