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Comparison of Prostate MRI Lesion Segmentation Agreement Between Multiple Radiologists and a Fully Automatic Deep Learning System.
Schelb, Patrick; Tavakoli, Anoshirwan Andrej; Tubtawee, Teeravut; Hielscher, Thomas; Radtke, Jan-Philipp; Görtz, Magdalena; Schütz, Viktoria; Kuder, Tristan Anselm; Schimmöller, Lars; Stenzinger, Albrecht; Hohenfellner, Markus; Schlemmer, Heinz-Peter; Bonekamp, David.
Afiliação
  • Schelb P; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Tavakoli AA; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Tubtawee T; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Hielscher T; Division of Biostatistics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Radtke JP; Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Görtz M; Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Schütz V; Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Kuder TA; Division of Medical Physics, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Schimmöller L; University Dusseldorf, Medical Faculty, Department of Diagnostic and Interventional Radiology, Dusseldorf, Germany.
  • Stenzinger A; Institute of Pathology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Hohenfellner M; Department of Urology, University of Heidelberg Medical Center, Heidelberg, Germany.
  • Schlemmer HP; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Bonekamp D; Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Rofo ; 193(5): 559-573, 2021 May.
Article em En | MEDLINE | ID: mdl-33212541
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próstata / Imageamento por Ressonância Magnética / Radiologistas / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Rofo Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Próstata / Imageamento por Ressonância Magnética / Radiologistas / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans / Male Idioma: En Revista: Rofo Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Alemanha