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Evaluation of real-time tumor contour prediction using LSTM networks for MR-guided radiotherapy.
Lombardo, Elia; Rabe, Moritz; Xiong, Yuqing; Nierer, Lukas; Cusumano, Davide; Placidi, Lorenzo; Boldrini, Luca; Corradini, Stefanie; Niyazi, Maximilian; Reiner, Michael; Belka, Claus; Kurz, Christopher; Riboldi, Marco; Landry, Guillaume.
Afiliação
  • Lombardo E; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Rabe M; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Xiong Y; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Nierer L; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Cusumano D; Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome 00168, Italy.
  • Placidi L; Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome 00168, Italy.
  • Boldrini L; Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome 00168, Italy.
  • Corradini S; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Niyazi M; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Reiner M; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Belka C; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany; German Cancer Consortium (DKTK), Munich 81377, Germany.
  • Kurz C; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany.
  • Riboldi M; Department of Medical Physics, Faculty of Physics, Ludwig-Maximilians-Universität München, Garching b. München 85748, Germany.
  • Landry G; Department of Radiation Oncology, University Hospital, LMU Munich, Munich 81377, Germany. Electronic address: guillaume.landry@med.uni-muenchen.de.
Radiother Oncol ; 182: 109555, 2023 05.
Article em En | MEDLINE | ID: mdl-36813166
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Radiother Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Radiother Oncol Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha