Djamel Dabli

For avid glucose tumors, the SUV peak is the most reliable parameter for [18F]FDG-PET/CT quantification, regardless of acquisition time

Avigaëlle Sher, Franck Lacœuille, Pacôme Fosse et al. · EJNMMI Research · 2016 · 120 citations · Full text

Medicine, Nuclear Medicine, Radiology +17

Comparison of two deep learning image reconstruction algorithms in chest CT images: A task-based image quality assessment on phantom data

Joël Greffier, Julien Frandon, Salim Si‐Mohamed et al. · Diagnostic and Interventional Imaging · 2021 · 68 citations

Medicine, Biomedical Engineering, Radiology +17

Comparison of two versions of a deep learning image reconstruction algorithm on CT image quality and dose reduction: A phantom study

Joël Greffier, Djamel Dabli, Julien Frandon et al. · Medical Physics · 2021 · 56 citations

Veterinary Medicine, Radiology, Biomedical Imaging +16

Effect of a new deep learning image reconstruction algorithm for abdominal computed tomography imaging on image quality and dose reduction compared with two iterative reconstruction algorithms: a phantom study

Joël Greffier, Djamel Dabli, Aymeric Hamard et al. · Quantitative Imaging in Medicine and Surgery · 2021 · 54 citations · Full text

Medicine, Radiology, Biomedical Imaging +16

Impact of an artificial intelligence deep‐learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study

Joël Greffier, Salim Si‐Mohamed, Julien Frandon et al. · Medical Physics · 2022 · 50 citations · Full text

Medicine, Radiology, Diagnostic Imaging +16