Abstract
Image segmentation is becoming a component of medical image processing with a significant role to analyze gross anatomy, to locate an infirmity and to plan the surgical procedures. Segmentation of brain magnetic resonance Imaging (MRI) is of increasing importance for the accurate diagnosis. For this reason, precise and accurate segmentation of brain MRI is a challenging task. In this paper we propose an approach for brain segmentation from MRI. Our method relies on a modified version of the U-Net convolutional neural network. Experiments performed on high grade brain cancer MRI demonstrate the effectiveness of the proposed approach for high grade brain cancer segmentation.
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