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Comparison of CT and MRI images for the prediction of soft-tissue sarcoma grading and lung metastasis via a convolutional neural networks model
Affiliation:1. Department of Radiology, Baoji Center Hospital, Baoji, 721008, Shaanxi, China;2. Department of Radiology, Baoji Hi-Tech People''s Hospital, Baoji, 721013, Shaanxi, China;1. Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, the First Affiliated Hospital, Sun Yat-Sen University, No 58 Zhongshan Er Road, 510080, PR China;2. Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The Seventh Affiliated Hospital, Sun-yat Sen University, No.628, Zhenyuan Road, Xinhu Street, Guangming New District, Shenzhen, 200090, PR China;3. Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The Eastern Hospital of The First Affiliated Hospital, Sun-yat Sen University, No. 183 Huangpu East Road, Huangpu District, Guangzhou, 510700, PR China;1. Department of Diagnostic and Interventional Radiology of the University Medical Center of the Johannes Gutenberg-University Mainz, Germany;2. Institute of Computer Science of the Johannes Gutenberg-University Mainz, Germany;3. Department of Internal Medicine III (Hematology, Oncology, Pneumology) of the University Medical Center of the Johannes Gutenberg-University Mainz, Germany;4. Department of Diagnostic and Interventional Radiology of the University Hospital of Cologne, Germany;1. Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany;2. Institute of Innovative Radiotherapy (iRT), Department of Radiation Sciences (DRS), Helmholtz Zentrum München, Neuherberg, Germany;3. Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Germany;4. Department for Bioinformatics and Computational Biology, Informatik 12, Technical University of Munich (TUM), Garching, Germany;5. University of Washington, Department of Radiation Oncology, Seattle, United States;6. Department of Radiology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany;7. Institut für Medizinische Statistik und Epidemiologie, Technical University of Munich (TUM), Munich, Germany;8. Institute for Advanced Study (IAS), Technical University of Munich (TUM), Germany;9. University of Washington, Department of Radiology, Seattle, United States;1. Department of Radiology, Chris Hani Baragwanath Academic Hospital, Johannesburg, South Africa;2. Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa;3. Department of Radiology, Children''s Hospital of Philadelphia, Pennsylvania, USA;4. Division of Infectious Diseases, Department of Internal Medicine, Chris Hani Baragwanath Academic Hospital, Johannesburg, South Africa;1. Department of Radiology, Graduate School of Medical and Dental Sciences, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima 890-8544, Japan;2. Department of Radiology, Division of Nuclear Medicine and PET Center, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 Japan;3. Department of Radiology, Kindai University Faculty of Medicine, 377-2 Ohnohigashi, Osakasayama, Osaka 589-8511, Japan;4. Department of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan;5. Department of Radiology, National Center for Global Health and Medicine, 1-21-1, Toyama, Shinjyuku-ku, Tokyo, 162-8655, Japan;6. Division of Radiology, Department of Pathophysiological and Therapeutic Science, Tottori University Faculty of Medicine, 36-1 Nishicho, Yonago, Tottori, 683-8504, Japan
Abstract:
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