计算机应用与软件2024，Vol.41Issue(12)：214-222,9.DOI:10.3969/j.issn.1000-386x.2024.12.031
基于混合损失注意力的CT气胸自动分割与量化
ACCURATE CT PNEUMOTHORAX SEGMENTATION AND VOLUME QUANTIFICATION BASED ON ATTENTION MIX-LOSS
唐琴 1刘志勤 1王庆凤 1黄俊 1薛博 1周莹2
作者信息
- 1. 西南科技大学计算机科学与技术学院 四川 绵阳 621010
- 2. 绵阳市中心医院放射科 四川 绵阳 621010
- 折叠
摘要
Abstract
The timely diagnosis of CT pneumothorax is particularly important.In this paper,an automatic segmentation and quantification method for CT pneumothorax is proposed.The threshold method was used to segment lung field to remove the influence of complex environment in lung field on CT pneumothorax segmentation.The pneumothorax was segmented based on Ma_Unet(Mixloss attention U_Net),and the shape,size and location information of the target area were automatically learned to alleviate the problem of data imbalance and optimize network training.The pneumothorax volume and lung compression ratio algorithm were proposed to achieve pixel level accurate CT pneumothorax volume quantification.The experimental results on the created Seg-CT-Pne test set show that the accuracy of proposed method is 99.96%,which is superior to the existing threshold method,U_Net and nnU-Net,and realizes the CT pneumothorax volume quantitative and lung compression ratio calculation.The whole automatic segmentation and quantization process only takes 18.87 s on average,and the mean difference in CT pneumothorax volume is only 4.47%,which meet the clinical needs.关键词
深度学习/CT气胸分割/混合损失/CT气胸体积量化Key words
Deep learning/CT pneumothorax segmentation/Mixing loss/CT pneumothorax volume quantification分类
信息技术与安全科学引用本文复制引用
唐琴,刘志勤,王庆凤,黄俊,薛博,周莹..基于混合损失注意力的CT气胸自动分割与量化[J].计算机应用与软件,2024,41(12):214-222,9.
