Vesselness-guided variational segmentation of cellular networks from 3D micro-CT

Advances in imaging techniques lead to nondestructive 3D visualization of biological tissue at a sub-cellular scale. As a consequence, new demands emerge to segment complex structures. For instance, synchrotron radiation micro-CT, makes it possible to image the lacunar-canalicular porosity in bone tissue. This structure contains a dense network of slender channels interconnecting the cells. Their size (~300-600 nanometers in diameter) is at the limit of the acquisition system resolution (280 nm) making their detection difficult. In this work is proposed a variational region growing segmentation method adapted for cellular networks. To control the evolution of the segmentation through tubular structures a vesselness map is introduced in the expression of the functional to minimize. The method is tested on synthetic images and applied to experimental data.