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The pseudo-label scheme in breast tumor classification based on BI-RADS features
Zhang, Fan1; Huang, Qinghua1; Li, Xuelong2; Huang, Qinghua (qhhuang@scut.edu.cn)
2018-02-22
会议名称10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
会议录名称Proceedings - 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2017
卷号2018-January
页码1-5
会议日期2017-10-14
会议地点Shanghai, China
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序2
摘要

The proposed method employs the Breast Imaging Reporting and Data System (BI-RADS) feature to classify the breast tumor. Compared with the ultrasound breast tumor classification methods based on the image, the 'semantic gap' between the clinical feature and image feature is eliminated. In order to address the shortage of the labeled data, the pseudo-labeled scheme based on SVM is designed. The SVM classifier is trained by few labeled samples, and the hybrid dataset which contains the pseudo-labeled sample marked by SVM and few labeled samples is adopted to train the decision tree. 500 ultrasound breast tumor cases are collected to evaluate the proposed method. According to the result of the experiment, compared with the decision tree trained by the labeled dataset only, the accuracy of decision tree train by hybrid dataset improves 2.65%, the NPV improves 7.00%, and the Sensitivity increases 3.30%. © 2017 IEEE.

作者部门光学影像学习与分析中心
DOI10.1109/CISP-BMEI.2017.8302288
收录类别EI
ISBN号9781538619377
语种英语
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30316
专题光学影像学习与分析中心
通讯作者Huang, Qinghua (qhhuang@scut.edu.cn)
作者单位1.School of Electronic and Information Engineering, South China University of Technology, Guangzhou; 510641, China
2.Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China
推荐引用方式
GB/T 7714
Zhang, Fan,Huang, Qinghua,Li, Xuelong,et al. The pseudo-label scheme in breast tumor classification based on BI-RADS features[C]:Institute of Electrical and Electronics Engineers Inc.,2018:1-5.
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