Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2012

Bjoern Menze (1) , Andras Jakab (2) , Stefan Bauer (3) , Mauricio Reyes (3) , Marcel Prastawa (4) , Koen van Leemput (5, 6)

1 ASCLEPIOS - Analysis and Simulation of Biomedical Images
2 CIR lab - Computational Image Analysis and Radiology
3 ISTB - Institute for Surgical Technology and Biomechanics [Bern]
4 SCI Institute - Scientific Computing and Imaging Institute
5 CSAIL - Computer Science and Artificial Intelligence Laboratory [Cambridge]
6 Massachusetts General Hospital - Department of radiology

Because of their unpredictable appearance and shape, segmenting brain tumors from multi-modal imaging data is one of the most challenging tasks in medical image analysis. Although many different segmentation strategies have been proposed in the literature, it is hard to compare existing methods because the validation datasets that are used differ widely in terms of input data (structural MR contrasts; perfusion or diffusion data; ...), the type of lesion (primary or secondary tumors; solid or infiltratively growing), and the state of the disease (pre- or post-treatment). In order to gauge the current state-of-the-art in automated brain tumor segmentation and compare between different methods, we are organizing a Multimodal Brain Tumor Segmentation (BRATS) challenge that is held in conjunction with the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2012) on October 1st, 2012 in Nice, France.

Domaines: Informatique

Bjoern Menze, Andras Jakab, Stefan Bauer, Mauricio Reyes, Marcel Prastawa, et al.. Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2012. Bjoern Menze and Andras Jakab and Mauricio Reyes and Stefan Bauer and Marcel Prastawa and Koen Van Leemput. MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS), Oct 2012, Nice, France. MICCAI, pp.77, 2012. ⟨hal-00912935⟩