Brain tumor segmentation in multi ‐spectral MRI using convolutional neural networks (CNN)

This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. The research presents a deep CNN to segment brain tumor in MRI. Proposed architecture consists of multiple CNN layers connected in sequential order using Convolutional feature maps at peer level. Experiments on BRATS 2015 exhibit promising results.
Source: Microscopy Research and Technique - Category: Laboratory Medicine Authors: Tags: RESEARCH ARTICLE Source Type: research