Xianhai Huang, L. Ling, Qinghua Huang, Yidi Lin, Xingzhang Long, Longzhong Liu
{"title":"Web-based training for radiologists of breast ultrasound","authors":"Xianhai Huang, L. Ling, Qinghua Huang, Yidi Lin, Xingzhang Long, Longzhong Liu","doi":"10.1109/CISP-BMEI.2017.8302273","DOIUrl":null,"url":null,"abstract":"Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"83 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8302273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Breast cancer is still considered as the most common form of cancer as well as the leading causes of cancer deaths among women all over the world. Fortunately, the mortality of breast cancer can be significantly reduced via the early detection and diagnosis of breast cancer. As one of the most continually used diagnosis tools, ultrasonography (US) scan plays an important role in the detection and classification of the breast tumor. In this paper, we introduce a large breast ultrasound image database which stored breast ultrasound images and pathology results from breast tumor patients as well as their clinic diagnostic information. Furthermore, we design a web-based training system based on the database using a feature scoring scheme which based on the fifth edition of Breast Imaging Reporting and Data System (BI-RADS) lexicon for US. This online training system (new web-based teaching framework) automatically creates case-based exercises to train and guide the newly employed or resident sonographers for diagnosis of breast cancer using breast ultrasound images based on the BI-RADS.