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Deep learning-based acceleration of Compressed Sense MR imaging of the ankle.
Foreman, Sarah C; Neumann, Jan; Han, Jessie; Harrasser, Norbert; Weiss, Kilian; Peeters, Johannes M; Karampinos, Dimitrios C; Makowski, Marcus R; Gersing, Alexandra S; Woertler, Klaus.
Afiliação
  • Foreman SC; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany. sarah.foreman@tum.de.
  • Neumann J; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Han J; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Harrasser N; Department of Orthopaedic Surgery, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Weiss K; Philips GmbH, Röntgenstrasse 22, 22335, Hamburg, Germany.
  • Peeters JM; Philips Healthcare, Veenpluis 4-6, Building QR-0.113, 5684, Best, PC, Netherlands.
  • Karampinos DC; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Makowski MR; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Gersing AS; Department of Radiology, Klinikum Rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675, Munich, Germany.
  • Woertler K; Department of Neuroradiology, University Hospital Munich (LMU), Marchioninistrasse 15, 81377, Munich, Germany.
Eur Radiol ; 32(12): 8376-8385, 2022 Dec.
Article em En | MEDLINE | ID: mdl-35751695
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Artefatos / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Artefatos / Aprendizado Profundo Tipo de estudo: Guideline / Observational_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article