RGA-Unet:一种基于残差分组卷积和卷积块注意模块的改进U-net分割模型,用于脑肿瘤MRI图像分割

Siyi Xun, Yan Zhang, Sixu Duan, Huachao Chen, Mingwei Wang, Jiangang Chen, T.W.K. Tan
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引用次数: 0

摘要

陈华超澳门理工大学应用科学学院p2213945@mpu.edu.mo王明伟杭州师范大学附属医院心血管内科杭州师范大学临床医学院杭州心血管病研究所wmw990556@hznu.edu.cn陈建刚华东师范大学通信与电子工程学院上海市多维信息处理重点实验室教育部中医药智能康复工程研究中心jgchen@cee.ecnu.edu.cn
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RGA-Unet: An improved U-net segmentation model based on residual grouped convolution and convolutional block attention module for brain tumor MRI image segmentation
Huachao Chen School of Faculty of Applied Sciences, Macao Polytechnic University p2213945@mpu.edu.mo Mingwei Wang Department of Dardiovascular Medicine, Affiliated Hospital of Hangzhou Normal University, Clinical School of Medicine, Hangzhou Normal University, Hangzhou Institute of Cardiovascular Diseases, wmw990556@hznu.edu.cn Jiangang Chen Shanghai Key Laboratory of Multidimensional Information Processing, School of Communication & Electronic Engineering, East China Normal University, Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education jgchen@cee.ecnu.edu.cn
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