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This article presents a multiscale patch based convolutional neural networkfor 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 2017segmentation challenge where we obtained dice scores of 0.755, 0.900, 0.782 and95% Hausdorff distance of 3.63mm, 4.10mm, and 6.81mm for enhanced tumor core,whole tumor and tumor core respectively.

A Multiscale Patch Based Convolutional Network for Brain Tumor Segmentation