A Multiscale Patch Based Convolutional Network for Brain Tumor Segmentation

10/06/2017

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This article presents a multiscale patch based convolutional neural network for the automatic segmentation of brain tumors in multi-modality 3D MR images. We use multiscale deep supervision and inputs to train a convolutional network. We evaluate the effectiveness of the proposed approach on the BRATS 2017 segmentation challenge where we obtained dice scores of 0.755, 0.900, 0.782 and 95 whole tumor and tumor core respectively.

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A Multiscale Patch Based Convolutional Network for Brain Tumor Segmentation

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