In this paper we address the object recognition problem in a probabilistic framework to detect and describe object appearance through image features organized by means of active c...
Image segmentation is conventionally formulated as a pixellabeling problem, in which “hard” decisions have to be made to partition pixels into regions. As image segmentation i...
Abstract. A new algorithm is presented for the automatic segmentation of Multiple Sclerosis (MS) lesions in 3D MR images. It builds on the discriminative random decision forest fra...
Ezequiel Geremia, Bjoern H. Menze, Olivier Clatz, ...
This paper introduces a novel statistical mixture model for probabilistic grouping of distributional histogram data. Adopting the Bayesian framework, we propose to perform anneale...
In this paper, we propose a hybrid approach for the automatic three-dimensional segmentation of coronary arteries using multi-scale vessel filtering and a Bayesian probabilistic ...
Yan Yang, Allen Tannenbaum, Don P. Giddens, Arthur...