计算机与数字工程2025，Vol.53Issue(1)：228-233,239,7.DOI:10.3969/j.issn.1672-9722.2025.01.041
基于注意力机制的三维肿瘤图像分割算法
3D Tumor Image Segmentation Algorithm Based on Attention Mechanism
摘要
Abstract
Automatic segmentation of brain tumor regions from multiple modes of MRI can effectively assist doctors in diagno-sis and treatment.A 3D end-to-end U-shaped network segmentation method is proposed to solve the problem that the 2D series net-work only focuses on local information and ignores the spatial consistency of different modalities.Firstly,a channel space mixed do-main attention mechanism is added in the encoder to realize feature extraction enhancement.Secondly,the operation mechanism of up-sampling and down-sampling is improved to prevent information loss.Finally,in order to fuse global information,balance the loss of different levels and speed up network training,depth supervision is introduced to the decoder part.The experimental results based on BraTS2021 data set show that Dice's similarity coefficient,sensitivity and HD95 distance reached 85.92%,92.04%and 17.47,respectively,which shows good accuracy in multi-modal tumor segmentation and edge contour.关键词
注意力机制/3D Unet网络/核磁共振图像/深度监督算法Key words
attentional mechanisms/3D Unet network/magnetic resonance imaging/depth monitoring algorithm分类
信息技术与安全科学引用本文复制引用
刘晓丽,程晓荣..基于注意力机制的三维肿瘤图像分割算法[J].计算机与数字工程,2025,53(1):228-233,239,7.基金项目
中央高校基本科研业务费专项资金(编号:2020MS122)资助. （编号:2020MS122）
