Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2013

Abstract : 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 Image Segmentation (BRATS) challenge that is held in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2013) on September 22nd, 2013 in Nagoya, Japan.
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Bjoern Menze and Mauricio Reyes and Andras Jakab and Elisabeth Gerstner and Justin Kirby and Keyvan Farahani. MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS), Sep 2013, Nagoya, Japan. MICCAI, pp.57, 2013
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Bjoern Menze, Mauricio Reyes, Andras Jakab, Elisabeth Gerstner, Justin Kirby, et al.. Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2013. Bjoern Menze and Mauricio Reyes and Andras Jakab and Elisabeth Gerstner and Justin Kirby and Keyvan Farahani. MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS), Sep 2013, Nagoya, Japan. MICCAI, pp.57, 2013. 〈hal-00912934〉

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