We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Deforming a digital atlas towards a patient image allows the simultaneous segmentation of several structures. Such an intersubject registration is difficult as the deformations to ...
We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
Abstract. This paper addresses the problem of automatically segmenting bone structures in low resolution clinical MRI datasets. The novel aspect of the proposed method is the combi...
Abstract. We propose new ideas and efficient algorithms towards bridging the gap between bag-of-features and constellation descriptors for image matching. Specifically, we show ho...