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Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropout.
Klanecek, Zan; Wagner, Tobias; Wang, Yao-Kuan; Cockmartin, Lesley; Marshall, Nicholas; Schott, Brayden; Deatsch, Ali; Studen, Andrej; Hertl, Kristijana; Jarm, Katja; Krajc, Mateja; Vrhovec, Milos; Bosmans, Hilde; Jeraj, Robert.
Afiliação
  • Klanecek Z; University of Ljubljana, Faculty of Mathematics and Physics, Medical Physics, Ljubljana, Slovenia.
  • Wagner T; KU Leuven, Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, Leuven, Belgium.
  • Wang YK; KU Leuven, Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, Leuven, Belgium.
  • Cockmartin L; UZ Leuven, Department of Radiology, Leuven, Belgium.
  • Marshall N; KU Leuven, Department of Imaging and Pathology, Division of Medical Physics & Quality Assessment, Leuven, Belgium.
  • Schott B; UZ Leuven, Department of Radiology, Leuven, Belgium.
  • Deatsch A; University of Wisconsin-Madison, Department of Medical Physics, Madison, United States of America.
  • Studen A; University of Wisconsin-Madison, Department of Medical Physics, Madison, United States of America.
  • Hertl K; University of Ljubljana, Faculty of Mathematics and Physics, Medical Physics, Ljubljana, Slovenia.
  • Jarm K; Jozef Stefan Institute, Ljubljana, Slovenia.
  • Krajc M; Institute of Oncology Ljubljana, Ljubljana, Slovenia.
  • Vrhovec M; Institute of Oncology Ljubljana, Ljubljana, Slovenia.
  • Bosmans H; Institute of Oncology Ljubljana, Ljubljana, Slovenia.
  • Jeraj R; Institute of Oncology Ljubljana, Ljubljana, Slovenia.
Phys Med Biol ; 68(11)2023 05 22.
Article em En | MEDLINE | ID: mdl-37137317
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research Idioma: En Ano de publicação: 2023 Tipo de documento: Article