计算机应用与软件2024，Vol.41Issue(7)：136-144,9.DOI:10.3969/j.issn.1000-386x.2024.07.021
基于YOLOv3的乳腺X线图像肿块检测方法
YOLOV3-BASED BREAST MASS DETECTION METHOD IN MAMMOGRAPHY
摘要
Abstract
Mammography is internationally recognized as an effective screening tool for early breast cancer.This paper proposes a mammographic mass detection method based on YOLOv3 network.The method could complete mass detection of the whole image at a faster speed while ensuring accuracy.By applying transfer learning technology,the mass lesion detection knowledge learned from the digitized mammograms were transferred to the full-field digital mammograms,which effectively solved the current lack of full-field digital mammography datasets.The five-fold cross-validation method was used for evaluation based on DDSM and INbreast datasets.Through extensive experiments,the obtained average accuracy of the mass detection over the five folds is 81.34％.关键词
深度学习/YOLOv3/乳腺X线图像/肿块检测/迁移学习Key words
Deep learning/YOLOv3/Mammography/Mass detection/Transfer learning分类
信息技术与安全科学引用本文复制引用
潘以轩,陈智丽,高皓,张辉,夏兴华..基于YOLOv3的乳腺X线图像肿块检测方法[J].计算机应用与软件,2024,41(7):136-144,9.基金项目
国家自然科学基金项目(61602322) （61602322）
辽宁省自然科学基金项目(20180550059) （20180550059）
辽宁省教育厅重点攻关项目(lnzd201904). （lnzd201904）
