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Enhancing 3D U-Net with Residual and Squeeze-and-Excitation Attention Mechanisms for Improved Brain Tumor Segmentation in Multimodal MRI

Yao-Tien Chen Nisar Ahmad Khursheed Aurangzeb

Computer Modeling in Engineering & Sciences2025，Vol.144Issue(7)：P.1197-1224,28.

Computer Modeling in Engineering & Sciences2025，Vol.144Issue(7)：P.1197-1224,28.DOI:10.32604/cmes.2025.066580

Enhancing 3D U-Net with Residual and Squeeze-and-Excitation Attention Mechanisms for Improved Brain Tumor Segmentation in Multimodal MRI

Yao-Tien Chen ¹Nisar Ahmad ¹Khursheed Aurangzeb²

作者信息

1. International Ph.D.Program in Innovative Technology of Biomedical Engineering and Medical Devices,Ming Chi University of Technology,New Taipei City,243303,Taiwan
2. Department of Computer Engineering,College of Computer and Information Sciences,King Saud University,P.O.Box 51178,Riyadh,11543,Saudi Arabia
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摘要

关键词

3D MRI/artificial intelligence/deep learning/AI in healthcare/attention mechanism/U-Net/medical image analysis/brain tumor segmentation/BraTS 2021/BraTS 2020

分类

医药卫生

引用本文复制引用

Yao-Tien Chen,Nisar Ahmad,Khursheed Aurangzeb..Enhancing 3D U-Net with Residual and Squeeze-and-Excitation Attention Mechanisms for Improved Brain Tumor Segmentation in Multimodal MRI[J].Computer Modeling in Engineering & Sciences,2025,144(7):P.1197-1224,28.

基金项目

the National Science and Technology Council(NSTC)of the Republic of China,Taiwan,for financially supporting this research under Contract No.NSTC 112-2637-M-131-001. （NSTC）

Computer Modeling in Engineering & Sciences

ISSN：1526-1492

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