Zhike Yi, A. Hao, Wenfeng Song, Hongyi Li, Bowen Li
{"title":"基于深度学习的超声图像智能甲状腺结节诊断系统","authors":"Zhike Yi, A. Hao, Wenfeng Song, Hongyi Li, Bowen Li","doi":"10.1109/ICVRV.2017.00038","DOIUrl":null,"url":null,"abstract":"At present, thyroid cancer has become a serious global public health problem, and ultrasound is the most important imaging method to assess thyroid nodules. But ultrasound diagnostic results of thyroid disease are susceptible to doctors' experiences, levels, status and other factors. So it needs intelligent diagnostic system to assist the doctors to make more objective qualitative and quantitative analyses, to reduce the impact of subjective experience on the diagnostic results. In this paper, a deep learning algorithm for thyroid nodule risk assessment based on ultrasound images is proposed, and an intelligent diagnostic system of thyroid ultrasound image based on this algorithm is constructed. As an aided diagnostic tool, the system is easy to use and can significantly improve the accuracy for determination of thyroid cancer. To verify the effectiveness of the system, we collaborate with the Peking Union Medical College Hospital to test this system.","PeriodicalId":187934,"journal":{"name":"2017 International Conference on Virtual Reality and Visualization (ICVRV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Novel Intelligent Thyroid Nodule Diagnosis System over Ultrasound Images Based on Deep Learning\",\"authors\":\"Zhike Yi, A. Hao, Wenfeng Song, Hongyi Li, Bowen Li\",\"doi\":\"10.1109/ICVRV.2017.00038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, thyroid cancer has become a serious global public health problem, and ultrasound is the most important imaging method to assess thyroid nodules. But ultrasound diagnostic results of thyroid disease are susceptible to doctors' experiences, levels, status and other factors. So it needs intelligent diagnostic system to assist the doctors to make more objective qualitative and quantitative analyses, to reduce the impact of subjective experience on the diagnostic results. In this paper, a deep learning algorithm for thyroid nodule risk assessment based on ultrasound images is proposed, and an intelligent diagnostic system of thyroid ultrasound image based on this algorithm is constructed. As an aided diagnostic tool, the system is easy to use and can significantly improve the accuracy for determination of thyroid cancer. To verify the effectiveness of the system, we collaborate with the Peking Union Medical College Hospital to test this system.\",\"PeriodicalId\":187934,\"journal\":{\"name\":\"2017 International Conference on Virtual Reality and Visualization (ICVRV)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Virtual Reality and Visualization (ICVRV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRV.2017.00038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Virtual Reality and Visualization (ICVRV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRV.2017.00038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Intelligent Thyroid Nodule Diagnosis System over Ultrasound Images Based on Deep Learning
At present, thyroid cancer has become a serious global public health problem, and ultrasound is the most important imaging method to assess thyroid nodules. But ultrasound diagnostic results of thyroid disease are susceptible to doctors' experiences, levels, status and other factors. So it needs intelligent diagnostic system to assist the doctors to make more objective qualitative and quantitative analyses, to reduce the impact of subjective experience on the diagnostic results. In this paper, a deep learning algorithm for thyroid nodule risk assessment based on ultrasound images is proposed, and an intelligent diagnostic system of thyroid ultrasound image based on this algorithm is constructed. As an aided diagnostic tool, the system is easy to use and can significantly improve the accuracy for determination of thyroid cancer. To verify the effectiveness of the system, we collaborate with the Peking Union Medical College Hospital to test this system.