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Decentralized Distributed Multi-institutional PET Image Segmentation Using a Federated Deep Learning Framework.
Shiri, Isaac; Vafaei Sadr, Alireza; Amini, Mehdi; Salimi, Yazdan; Sanaat, Amirhossein; Akhavanallaf, Azadeh; Razeghi, Behrooz; Ferdowsi, Sohrab; Saberi, Abdollah; Arabi, Hossein; Becker, Minerva; Voloshynovskiy, Slava; Gündüz, Deniz; Rahmim, Arman; Zaidi, Habib.
Afiliación
  • Shiri I; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Amini M; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Salimi Y; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Sanaat A; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Akhavanallaf A; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Razeghi B; Department of Computer Science.
  • Ferdowsi S; HES-SO, University of Geneva, Geneva.
  • Saberi A; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Arabi H; From the Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital.
  • Becker M; Division of Radiology, Geneva University Hospital, Geneva, Switzerland.
  • Voloshynovskiy S; Department of Computer Science.
  • Gündüz D; Faculty of Engineering, Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.
Clin Nucl Med ; 47(7): 606-617, 2022 Jul 01.
Article en En | MEDLINE | ID: mdl-35442222
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias de Cabeza y Cuello Tipo de estudio: Clinical_trials / Guideline Aspecto: Ethics Límite: Humans Idioma: En Revista: Clin Nucl Med Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias de Cabeza y Cuello Tipo de estudio: Clinical_trials / Guideline Aspecto: Ethics Límite: Humans Idioma: En Revista: Clin Nucl Med Año: 2022 Tipo del documento: Article Pais de publicación: Estados Unidos