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Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.
Greffier, Joël; Pastor, Maxime; Si-Mohamed, Salim; Goutain-Majorel, Cynthia; Peudon-Balas, Aude; Bensalah, Mourad Zoubir; Frandon, Julien; Beregi, Jean-Paul; Dabli, Djamel.
Affiliation
  • Greffier J; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France. Electronic address: joel.greffier@chu-nimes.fr.
  • Pastor M; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
  • Si-Mohamed S; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, 69100 Villeurbanne, France; Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, 69500 Bron, France.
  • Goutain-Majorel C; Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Peudon-Balas A; Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Bensalah MZ; Department of Medical Imaging, Centre Hospitalier de Perpignan, 66000 Perpignan, France.
  • Frandon J; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
  • Beregi JP; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
  • Dabli D; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, France.
Diagn Interv Imaging ; 105(3): 110-117, 2024 Mar.
Article in En | MEDLINE | ID: mdl-37949769
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, X-Ray Computed / Deep Learning Limits: Humans Language: En Journal: Diagn Interv Imaging Year: 2024 Document type: Article Country of publication: Francia
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tomography, X-Ray Computed / Deep Learning Limits: Humans Language: En Journal: Diagn Interv Imaging Year: 2024 Document type: Article Country of publication: Francia