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Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation.

Sun, Meijun; Li, Pengfei; Ren, Jinchang; Wang, Zheng

Authors

Meijun Sun

Pengfei Li

Zheng Wang



Abstract

Existing deep learning–based medical image segmentation methods have achieved gratifying progress, but they still suffer from the coarse boundaries with similar pixels of target. Because the boundary of medical images becomes blurred and the gradient is inconsistent and not apparent, high-resolution images are needed for more accurate segmentation. To tackle these problems, we propose an efficient multi-layer edge perception U-shaped structure for medical image segmentation. In this paper, we present a multi-layer edge perception network for describing more precise edges of medical targets. The U-structure architecture of our network embeds a multi-layer edge perception module, which has the following advantages: (1) connecting different scales and channels to help the network better learn the feature of the medical image via the combination of a pyramid structure and several edge perception modules; (2) a new downsampling block is designed to improve the network’s sensibility to the target boundary. We demonstrate the effectiveness of the proposed model on the DRIVE datasets, and achieve a Dice gain of 0.841 over other models. In this paper, we propose an efficient multi-layer edge perception U-shaped structure for medical image segmentation. A large number of experiments show that the performance of our proposed multi-layer edge perception U-shaped network is significantly better than the traditional segmented network structure.

Citation

SUN, M., LI, P., REN, J. and WANG, Z. 2023. Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation. Cognitive computation [online], 15(1), pages 348-358. Available from: https://doi.org/10.1007/s12559-022-10094-4

Journal Article Type Article
Acceptance Date Dec 4, 2022
Online Publication Date Jan 6, 2023
Publication Date Jan 31, 2023
Deposit Date Feb 23, 2023
Publicly Available Date Jan 7, 2024
Journal Cognitive computation
Print ISSN 1866-9956
Electronic ISSN 1866-9964
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 15
Issue 1
Pages 348-358
DOI https://doi.org/10.1007/s12559-022-10094-4
Keywords Deep medical segmentation; U-Structure network; Attention mechanism; Semantic segmentation
Public URL https://rgu-repository.worktribe.com/output/1862258

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Copyright Statement
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.





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