首页> Scientific reports> Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.

Automated classification of chondroid tumor using 3D U-Net and radiomics with deep features.

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第一作者： Tuan,Le Dinh

第一单位： Visual Analysis and Learning for Improved Diagnostics (VALID) Lab, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.

作者： Tuan,Le Dinh ^[1] ; Seungeun,Lee ^[2] ; Hyemin,Park ^[2] ; Sungwon,Lee ^[3] ; Hyeondeok,Choi ^[3] ; Keum San,Chun ^[1] ; Joon-Yong,Jung ^[4]

作者单位： Visual Analysis and Learning for Improved Diagnostics (VALID) Lab, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. ^[1] Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. ^[2] Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea.;Visual Analysis and Learning for Improved Diagnostics (VALID) Lab, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. ^[3] Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. jy.jung@songeui.ac.kr.;Visual Analysis and Learning for Improved Diagnostics (VALID) Lab, College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea. jy.jung@songeui.ac.kr. ^[4]

关键词 3D U-Net Chondroid tumors Computer-aided diagnosis Deep learning MRI images Machine learning algorithms Radiomics Tumor segmentation