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...
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...
A framework is proposed for the segmentation of brain tumors from MRI. Instead of training on pathology, the proposed method trains exclusively on healthy tissue. The algorithm att...
Given models for healthy brains, tumor segmentation can be seen as a process of detecting abnormalities or outliers that are present with certain image intensity and geometric prop...
Marcel Prastawa, Elizabeth Bullitt, Sean Ho, Guido...
In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation app...
Michael Wels, Gustavo Carneiro, Alexander Aplas,...