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Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.
Gardner, Mark; Bouchta, Youssef Ben; Mylonas, Adam; Mueller, Marco; Cheng, Chen; Chlap, Phillip; Finnegan, Robert; Sykes, Jonathan; Keall, Paul J; Nguyen, Doan Trang.
Afiliação
  • Gardner M; ACRF Image X Institute, The University of Sydney, Eveleigh, New South Wales, Australia.
  • Bouchta YB; ACRF Image X Institute, The University of Sydney, Eveleigh, New South Wales, Australia.
  • Mylonas A; ACRF Image X Institute, The University of Sydney, Eveleigh, New South Wales, Australia.
  • Mueller M; ACRF Image X Institute, The University of Sydney, Eveleigh, New South Wales, Australia.
  • Cheng C; ACRF Image X Institute, The University of Sydney, Eveleigh, New South Wales, Australia.
  • Chlap P; South Western Sydney Clinical School, University of New South Wales, Liverpool, New South Wales, Australia.
  • Finnegan R; Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia.
  • Sykes J; Liverpool Cancer Therapy Centre, Liverpool Hospital, Liverpool, New South Wales, Australia.
  • Keall PJ; Ingham Institute for Applied Medical Research, Liverpool, New South Wales, Australia.
  • Nguyen DT; Northern Sydney Cancer Centre, Royal North Shore Hospital, St Leonards, New South Wales, Australia.
Med Phys ; 50(7): 4206-4219, 2023 Jul.
Article em En | MEDLINE | ID: mdl-37029643
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Neoplasias de Cabeça e Pescoço Tipo de estudo: Diagnostic_studies / Observational_studies Limite: Humans Idioma: En Revista: Med Phys Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado Profundo / Neoplasias de Cabeça e Pescoço Tipo de estudo: Diagnostic_studies / Observational_studies Limite: Humans Idioma: En Revista: Med Phys Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália