Total variation super-resolution for 3D trabecular bone micro-structure segmentation

The analysis of the trabecular bone micro-structure plays an important role in studying bone fragility diseases such as osteoporosis. In this context, X-ray CT techniques are increasingly used to image bone micro-architecture. The aim of this paper is to improve the segmentation of the bone micro-structure for further bone quantification. We propose a joint super-resolution/segmentation method based on total variation with a convex constraint. The minimization is performed with the Alternating Direction Method of Multipliers (ADMM). The new method is compared with the bicubic interpolation method and the classical total variation regularization. All methods were tested on blurred, noisy and down-sampled 3D synchrotron micro-CT bone volumes. Improved segmentation is obtained with the proposed joint super-resolution/segmentation method.