Convolutional Neural Networks for the segmentation of hippocampal structures in postmortem MRI scans.

ABSTRACT:

Background

The hippocampus plays a crucial role in memory and is one of the first structures affected by Alzheimer's disease. Postmortem MRI offers a way to quantify the alterations by measuring the atrophy of the inner structures of the hippocampus. Unfortunately, the manual segmentation of hippocampal subregions required to carry out these measures is very time-consuming.

New method

In this study, we explore the use of fully automated methods relying on state-of-the-art Deep Learning approaches to produce these annotations. More specifically, we propose a new segmentation framework made of a set of encoder-decoder blocks embedding self-attention mechanisms and atrous spatial pyramidal pooling to produce better maps of the hippocampus and identify four hippocampal regions:

SUBMITTER: B N A 

PROVIDER: S-EPMC12308772 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature