Performing Accurate Rigid Kinematics Measurements from 3D in vivo Image Sequences through Median Consensus...

While focusing at accurate 3D joint kinematics, this paper explores the problem of how to perform a robust rigid registration for a sequence of object surfaces observed using standard 3D medical imaging techniques. Each object instance is assumed to give access to a polyhedral encoding of its boundary. We consider the case where object instances are noised with significant truncations and segmentation errors. The proposed method aims to tackle this problem in a global way, fully exploiting the duality between redundancy and complementarity of the available instances set. The algorithm operates through robust and simultaneous registration of all geometrical instances on a virtual instance accounting for their median consensus. When compared with standard robust techniques, trials reveal significant gains, as much in robustness as in accuracy. The considered applications are mainly focused on generating highly accurate kinematics in relation to the bone structures of the most complex joints - the tarsus and the carpus - for which no alternative examination techniques exist, enabling fine morphological analysis as well as access to internal joint motions.