This paper introduces a novel statistical mixture model for probabilistic clustering of histogram data and, more generally, for the analysis of discrete co occurrence data. Adoptin...
Image smoothing, segmentation and registration are three key processing steps in many computer vision applications. In this paper, we present a novel framework for achieving all t...
Abstract. In this paper, we propose a robust fully non-supervised method dedicated to the segmentation of the brain in T1-weighted MR images. The first step consists in the analysi...
Jean-Francois Mangin, Olivier Coulon, Vincent Frou...
We propose a semi-supervised model which segments and annotates images using very few labeled images and a large unaligned text corpus to relate image regions to text labels. Give...
This paper focuses on the detection and segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. The proposed method performs healthy tissue segmentation usin...