Abstract. This paper exposes a novel formulation of prior shape constraint incorporation for the level set segmentation of objects from corrupted images. Applicable to variational ...
So far global optimization techniques have been developed independently for the tasks of shape matching and image segmentation. In this paper we show that both tasks can in fact b...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...
We propose a variational framework for the integration of multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functional wi...
Daniel Cremers, Nir A. Sochen, Christoph Schnö...
Abstract. We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a c...