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ESA-Net:An Efficient and Lightweight Model for Medical Image Segmentation

Haiquan Liu Mingcan Cen Chong Zhang Angela An Shuxiang Song

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：248-262,15.

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：248-262,15.DOI:10.26599/BDMA.2025.9020053

ESA-Net:An Efficient and Lightweight Model for Medical Image Segmentation

Haiquan Liu ¹Mingcan Cen ¹Chong Zhang ²Angela An ²Shuxiang Song¹

作者信息

1. Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips,School of Electronic and Information Engineering,Guangxi Normal University,Guilin 541004,China||Key Laboratory of Integrated Circuits and Microsystems(Guangxi Normal University),Education Department of Guangxi Zhuang Autonomous Region,Guilin 541004,China
2. School of Information Technology,Deakin University,Burwood VIC 3125,Australia
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摘要

关键词

transformer/medical image segmentation/share attention/lightweight

Key words

transformer/medical image segmentation/share attention/lightweight

引用本文复制引用

Haiquan Liu,Mingcan Cen,Chong Zhang,Angela An,Shuxiang Song..ESA-Net:An Efficient and Lightweight Model for Medical Image Segmentation[J].大数据挖掘与分析（英文版）,2026,9(1):248-262,15.

基金项目

This work was supported by the National Natural Science Foundation of China(No.62366006). （No.62366006）

大数据挖掘与分析（英文版）

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