Exploration of the stages at which features should be extracted from MRI images using a CNN-based segmentation model

Abstract

Segmentation of major brain tissues from 3D medical images can contribute to improving diagnostic quality and reducing workload. This study aims to explore the proper structure to segment brain regions from MRI volumes. The dataset used was the preprocessed IXI dataset, and segmentation was performed on 46 regions from the head MRI images. Experimental results show that it is important to extract features in the first stage, when the resolution is large.