Abstract. We describe a new approach for estimating the posterior probability of tissue labels. Conventional likelihood models are combined with a curve length prior on boundaries,...
Abstract. For every segmentation task, prior knowledge about the object that shall be segmented has to be incorporated. This is typically performed either automatically by using la...
Margret Keuper, Robert Bensch, Karsten Voigt, Alex...
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
We propose a new approach to compute non-linear, intrinsic shape statistics and to incorporate them into a shape prior for an image segmentation task. Given a sample set of contou...
Guillaume Charpiat, Olivier D. Faugeras, Renaud Ke...