生物医学工程研究2025，Vol.44Issue(3)：135-142,8.DOI:10.19529/j.cnki.1672-6278.2025.03.01
基于改进YOLOv8的乳腺X射线图像肿瘤分割算法
Tumor segmentation algorithm in mammograms based on improved YOLOv8
摘要
Abstract
To improve the segmentation accuracy and efficiency of breast tumors under limited computing resources,we proposed a tumor segmentation algorithm for mammograms by improving the YOLOv8 model.Firstly,a feature extraction module PC-C3K2 was de-signed by pinwheel convolution(PConv)and C3K2 module to significantly expand the receptive field and reduce the number of model parameters.Secondly,the spatial channel decoupling downsampling module was utilized for downsampling,and the computational com-plexity was reduced by independently processing the spatial information and channel information.The experimental results on the IN-breast and the CBIS-DDSM datasets showed that the mAP50 value of the proposed algorithm reached 91.8%,and the number of param-eters could be reduced by 28%.The algorithm can significantly reduce the number of model parameters while improving the tumor seg-mentation accuracy of mammograms,which is of great significance for the early screening and diagnosis of breast tumors.关键词
YOLOv8/肿瘤分割/轻量化/乳腺肿瘤/乳腺X射线图像Key words
YOLOv8/Tumor segmentation/Lightweight/Breast tumor/Mammograms分类
医药卫生引用本文复制引用
张凌宇,丛金玉,李翔,王苹苹,刘坤孟,司兴勇,魏本征..基于改进YOLOv8的乳腺X射线图像肿瘤分割算法[J].生物医学工程研究,2025,44(3):135-142,8.基金项目
国家自然科学基金项目(62372280,62402297) （62372280,62402297）
山东省自然科学基金项目(2023QF094,2024MF139) （2023QF094,2024MF139）
青岛市科技惠民示范专项(23-2-8-smjk-2-nsh) （23-2-8-smjk-2-nsh）
齐鲁健康与卫生领军人才计划项目 （）
山东省青年科技人才托举工程 （）
山东中医药大学科学研究基金重点项目. （）
