{"title":"临床乳房x线摄影识别的建模","authors":"Kuo-Chung Chu, Po-Yao Tsai, Tien-Yu Chang, Yu-Shu Wu","doi":"10.1109/IRI49571.2020.00068","DOIUrl":null,"url":null,"abstract":"Breast cancer screening can detect and treat early, mammography is one of popular screening methods. Recognition of mammography image depends on the radiologist, but human interpretation of mammography image has its limitations. Recently, for precision medicine, deep learning technology is applied on medical images to reduce the risk of the interpretation on breast lesion types (BIRADS, Breast Imaging Reporting and Data System, divided into 0 to 6 categories). This study proposes a mammography recognition model that is based on deep learning method to support clinical diagnosis of breast cancer. The model is try to improve medical quality.","PeriodicalId":93159,"journal":{"name":"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling of Clinical Mammography Recognition\",\"authors\":\"Kuo-Chung Chu, Po-Yao Tsai, Tien-Yu Chang, Yu-Shu Wu\",\"doi\":\"10.1109/IRI49571.2020.00068\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Breast cancer screening can detect and treat early, mammography is one of popular screening methods. Recognition of mammography image depends on the radiologist, but human interpretation of mammography image has its limitations. Recently, for precision medicine, deep learning technology is applied on medical images to reduce the risk of the interpretation on breast lesion types (BIRADS, Breast Imaging Reporting and Data System, divided into 0 to 6 categories). This study proposes a mammography recognition model that is based on deep learning method to support clinical diagnosis of breast cancer. The model is try to improve medical quality.\",\"PeriodicalId\":93159,\"journal\":{\"name\":\"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IRI49571.2020.00068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRI49571.2020.00068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
乳腺癌筛查可以早期发现和治疗，乳房x光检查是流行的筛查方法之一。乳房x光图像的识别依赖于放射科医生，但人类对乳房x光图像的解释有其局限性。最近，在精准医疗方面，深度学习技术被应用于医学图像上，以降低对乳腺病变类型的解释风险(BIRADS, breast Imaging Reporting and Data System，分为0 - 6类)。本研究提出了一种基于深度学习方法的乳腺x线摄影识别模型，以支持乳腺癌的临床诊断。该模式旨在提高医疗质量。
Breast cancer screening can detect and treat early, mammography is one of popular screening methods. Recognition of mammography image depends on the radiologist, but human interpretation of mammography image has its limitations. Recently, for precision medicine, deep learning technology is applied on medical images to reduce the risk of the interpretation on breast lesion types (BIRADS, Breast Imaging Reporting and Data System, divided into 0 to 6 categories). This study proposes a mammography recognition model that is based on deep learning method to support clinical diagnosis of breast cancer. The model is try to improve medical quality.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
