An accurate 3D shape context based non-rigid registration method for mouse whole-body skeleton registration

Small animal image registration is challenging because of its joint structure, and posture and position difference in each acquisition without a standard scan protocol. In this paper, we face the issue of mouse whole-body skeleton registration from CT images. A novel method is developed for analyzing mouse hind-limb and fore-limb postures based on geodesic path descriptor and then registering the major skeletons and fore limb skeletons initially by thin-plate spline (TPS) transform based on the obtained geodesic paths and their enhanced correspondence fields. A target landmark correction method is proposed for improving the registration accuracy of the improved 3D shape context non-rigid registration method we previously proposed. A novel non-rigid registration framework, combining the skeleton posture analysis, geodesic path based initial alignment and 3D shape context model, is proposed for mouse whole-body skeleton registration. The performance of the proposed methods and framework was tested on 12 pairs of mouse whole-body skeletons. The experimental results demonstrated the flexibility, stability and accuracy of the proposed framework for automatic mouse whole body skeleton registration.