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Development and multi-institutional validation of a convolutional neural network to detect vertebral body mis-alignments in 2D x-ray setup images.
Petragallo, Rachel; Bertram, Pascal; Halvorsen, Per; Iftimia, Ileana; Low, Daniel A; Morin, Olivier; Narayanasamy, Ganesh; Saenz, Daniel L; Sukumar, Kevinraj N; Valdes, Gilmer; Weinstein, Lauren; Wells, Michelle C; Ziemer, Benjamin P; Lamb, James M.
Afiliación
  • Petragallo R; Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
  • Bertram P; Brainlab AG, Munich, Germany.
  • Halvorsen P; Department of Radiation Oncology, Beth Israel - Lahey Health, Burlington, Massachusetts, USA.
  • Iftimia I; Department of Radiation Oncology, Beth Israel - Lahey Health, Burlington, Massachusetts, USA.
  • Low DA; Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
  • Morin O; Department of Radiation Oncology, University of California San Francisco, San Francisco, California, USA.
  • Narayanasamy G; Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA.
  • Saenz DL; Department of Radiation Oncology, University of Texas HSC SA, San Antonio, Texas, USA.
  • Sukumar KN; Department of Radiation Oncology, Piedmont Healthcare, Atlanta, Georgia, USA.
  • Valdes G; Department of Radiation Oncology, University of California San Francisco, San Francisco, California, USA.
  • Weinstein L; Department of Radiation Oncology, Kaiser Permanente, South San Francisco, California, USA.
  • Wells MC; Department of Radiation Oncology, Piedmont Healthcare, Atlanta, Georgia, USA.
  • Ziemer BP; Department of Radiation Oncology, University of California San Francisco, San Francisco, California, USA.
  • Lamb JM; Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Med Phys ; 50(5): 2662-2671, 2023 May.
Article en En | MEDLINE | ID: mdl-36908243
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Clinical_trials / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Med Phys Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
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PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Clinical_trials / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Med Phys Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos