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Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.
Jun, Yohan; Park, Yae Won; Shin, Hyungseob; Shin, Yejee; Lee, Jeong Ryong; Han, Kyunghwa; Ahn, Sung Soo; Lim, Soo Mee; Hwang, Dosik; Lee, Seung-Koo.
Afiliación
  • Jun Y; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
  • Park YW; Department of Radiology, Harvard Medical School, Boston, MA, USA.
  • Shin H; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Shin Y; School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Lee JR; School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Han K; School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Ahn SS; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
  • Lim SM; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea. sungsoo@yuhs.ac.
  • Hwang D; Department of Radiology, Ewha Womans University College of Medicine, Seoul, Korea.
  • Lee SK; Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea. dosik.hwang@yonsei.ac.kr.
Eur Radiol ; 33(9): 6124-6133, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37052658
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias Meníngeas / Meningioma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias Meníngeas / Meningioma Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur Radiol Asunto de la revista: RADIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos