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Multi-institutional PET/CT image segmentation using federated deep transformer learning.
Shiri, Isaac; Razeghi, Behrooz; Vafaei Sadr, Alireza; Amini, Mehdi; Salimi, Yazdan; Ferdowsi, Sohrab; Boor, Peter; Gündüz, Deniz; Voloshynovskiy, Slava; Zaidi, Habib.
Afiliación
  • Shiri I; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
  • Razeghi B; Department of Computer Science, University of Geneva, Geneva, Switzerland.
  • Vafaei Sadr A; Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany; Department of Public Health Sciences, College of Medicine, The Pennsylvania State University, Hershey, PA 17033, USA.
  • Amini M; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
  • Salimi Y; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland.
  • Ferdowsi S; Department of Computer Science, University of Geneva, Geneva, Switzerland.
  • Boor P; Institute of Pathology, RWTH Aachen University Hospital, Aachen, Germany.
  • Gündüz D; Department of Electrical and Electronic Engineering, Imperial College London, UK.
  • Voloshynovskiy S; Department of Computer Science, University of Geneva, Geneva, Switzerland.
  • Zaidi H; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva, Switzerland; Geneva University Neurocenter, University of Geneva, Geneva, Switzerland; Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, The Netherlands; Department of Nucl
Comput Methods Programs Biomed ; 240: 107706, 2023 Oct.
Article en En | MEDLINE | ID: mdl-37506602
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias Tipo de estudio: Clinical_trials Aspecto: Ethics Límite: Humans Idioma: En Revista: Comput Methods Programs Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Irlanda
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Aprendizaje Profundo / Neoplasias Tipo de estudio: Clinical_trials Aspecto: Ethics Límite: Humans Idioma: En Revista: Comput Methods Programs Biomed Asunto de la revista: INFORMATICA MEDICA Año: 2023 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Irlanda