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Exploring Whether CNN-Based Segmentation Models Should Extract Features in Earlier or Later Stages for MRI Images

  • Hibiki Umeda,
  • Yuki Shinomiya

摘要

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.