Abstract. We introduce a generative probabilistic model for segmentation of tumors in multi-dimensional images. The model allows for different tumor boundaries in each channel, ref...
Bjoern H. Menze, Koenraad Van Leemput, Danial Lash...
In this paper, multi-modal Magnetic Resonance (MR) images are integrated into a tissue profile that aims at differentiating tumor components, edema and normal tissue. This is achi...
Validation and method of comparison for segmentation of magnetic resonance images (MRI) presenting pathology is a challenging task due to the lack of reliable ground truth. We prop...
Abstract-- We present a new method for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation me...
Jason J. Corso, Eitan Sharon, S. Dube, Suzie El-Sa...
This paper presents a Bayesian framework for generating inverse-consistent inter-subject large deformation transformations between two multi-modal image sets of the brain. In this...