We propose a semi-supervised image segmentation method that relies on a non-local continuous version of the min-cut algorithm and labels or seeds provided by a user. The segmentati...
Nawal Houhou, Xavier Bresson, Arthur Szlam, Tony F...
Combinatorial graph cut algorithms have been successfully applied to a wide range of problems in vision and graphics. This paper focusses on possibly the simplest application of gr...
In this paper we propose a Markov random field (MRF) based method for joint registration and segmentation of cardiac perfusion images, specifically the left ventricle (LV). MRFs ...
Segmentation of tree-like structure within medical imaging modalities, such as x-ray, MRI, ultrasound, etc., is an important step for analyzing branching patterns involved in many...
Abstract. Graph cut minimization formulates the segmentation problem as the liner combination of data and smoothness terms. The smoothness term is included in the energy formulatio...