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...
We propose a novel approach for shape-based segmentation based on a specially designed level set function format. This format permits us to better control the process of object re...
We present a novel variational approach to top-down image segmentation, which accounts for significant projective transformations between a single prior image and the image to be s...
We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. The shape prior energy is based on a shape distance popular with level se...
Abstract. In this paper we propose a new variational framework for image segmentation that incorporates the information of expected shape and a few points on the boundary into geod...
Yunmei Chen, Weihong Guo, Feng Huang, David Cliffo...