MEA-Net: multilayer edge attention network for medical image segmentation.

ABSTRACT: Medical image segmentation is a fundamental step in medical analysis and diagnosis. In recent years, deep learning networks have been used for precise segmentation. Numerous improved encoder-decoder structures have been proposed for various segmentation tasks. However, high-level features have gained more research attention than the abundant low-level features in the early stages of segmentation. Consequently, the learning of edge feature maps has been limited, which can lead to ambiguous boundaries of the predicted results. Inspired by the encoder-decoder network and attention mechanism, this study investigates a novel multilayer edge attention network (MEA-Net) to fully utilize the edge information in the encoding stages. MEA-Net comprises three major components: a feature encoder module

SUBMITTER: Liu H 

PROVIDER: S-EPMC9098486 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature