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Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.
Dratsch, Thomas; Korenkov, Michael; Zopfs, David; Brodehl, Sebastian; Baessler, Bettina; Giese, Daniel; Brinkmann, Sebastian; Maintz, David; Pinto Dos Santos, Daniel.
Afiliação
  • Dratsch T; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany. t.dratsch@mac.comn.
  • Korenkov M; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Zopfs D; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Brodehl S; Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany.
  • Baessler B; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zürich, Switzerland.
  • Giese D; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Brinkmann S; Department of General, Visceral and Cancer Surgery, University Hospital Cologne, Cologne, Germany.
  • Maintz D; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
  • Pinto Dos Santos D; Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937, Cologne, Germany.
Eur Radiol ; 31(4): 1812-1818, 2021 Apr.
Article em En | MEDLINE | ID: mdl-32986160
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Guideline Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Guideline Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article