Phantom-based performance comparison of two commercial deep learning CT reconstruction algorithms with super- and normal-resolution settings.
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| Title: | Phantom-based performance comparison of two commercial deep learning CT reconstruction algorithms with super- and normal-resolution settings. |
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| Authors: | Greffier J; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France. joel.greffier@chu-nimes.fr., Roy C; Diagnostic Imagery Department, Nouvel Hôpital Civil (NHC), Hôpitaux Universitaires de Strasbourg, Strasbourg, France., Dabli D; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France. djamel.dabli@chu-nimes.fr., Beregi JP; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France., Pastor M; IMAGINE UR UM 103, Montpellier University, Department of Medical Imaging, Nîmes University Hospital, Nîmes, France. |
| Source: | European radiology experimental [Eur Radiol Exp] 2026 Jan 26; Vol. 10 (1), pp. 9. Date of Electronic Publication: 2026 Jan 26. |
| Publication Type: | Journal Article; Comparative Study |
| Journal Info: | Publisher: SpringerOpen Country of Publication: England NLM ID: 101721752 Publication Model: Electronic Cited Medium: Internet ISSN: 2509-9280 (Electronic) Linking ISSN: 25099280 NLM ISO Abbreviation: Eur Radiol Exp Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2509-9280 |
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| DOI: | 10.1186/s41747-025-00670-2 |
