- Titre
- Contribution of a new super-resolution deep-learning image reconstruction algorithm coupled with an extended matrix to cardiac CT image quality
- Créateurs - sans rôle
- Joël Greffier - IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, FranceDjamel Dabli - IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, FranceFabien de Oliveira - IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, FranceJean-Paul Beregi - IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, 30029 Nîmes, FranceMickaël Ohana - Department of Diagnostic Imaging, Nouvel Hôpital Civil (NHC), Hôpitaux Universitaires de Strasbourg, 17, rue de la Porte-de-l'Hôpital, 67000 Strasbourg, France
- Détails de publication
- Diagnostic and interventional imaging, Vol.106(12), pp.438-440
- Éditeur
- Elsevier Masson SAS
- Nombre de pages
- 3
- Identifiants
- 99139982909311
- Unité académique
- Initial MAnagement & prevent of acute orGan failures IN critically ill patiEnts - IMAGINE
- Langue
- English
- Type de ressource
- Journal article
Article de revue
Contribution of a new super-resolution deep-learning image reconstruction algorithm coupled with an extended matrix to cardiac CT image quality
Diagnostic and interventional imaging, Vol.106(12), pp.438-440
01/12/2025
PMID: 40610340
Indicateurs
1 Consultations de la notice