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Can 1.25 mm thin-section images generated with Deep Learning Image Reconstruction technique replace standard-of-care 5 mm images in abdominal CT?
Cao, Jinjin; Mroueh, Nayla; Pisuchpen, Nisanard; Parakh, Anushri; Lennartz, Simon; Pierce, Theodore T; Kambadakone, Avinash R.
Afiliação
  • Cao J; Abdominal Radiology Division, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
  • Mroueh N; Abdominal Radiology Division, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
  • Pisuchpen N; Abdominal Radiology Division, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
  • Parakh A; Department of Radiology, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
  • Lennartz S; Abdominal Radiology Division, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
  • Pierce TT; Abdominal Radiology Division, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White 270, Boston, MA, 02114-2696, USA.
  • Kambadakone AR; Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany.
Abdom Radiol (NY) ; 48(10): 3253-3264, 2023 10.
Article em En | MEDLINE | ID: mdl-37369922
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article