Skip to content
Log in
Sponsored AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI AI AM CLAUDE, A Beginner's Guide: Learn the basics of working with AI

Author

J. Greffier

View on Semantic Scholar

4 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access Sep 2026

Optimization of spectral photon-counting CT reconstruction parameters for improved detection of peritoneal metastases compared with energy-integrating detector dual-energy CT: a phantom study

To determine the best combination of reconstruction parameters on a spectral photon-counting CT (SPCCT) system to improve detection of peritoneal metastases (PMs) on virtual monoenergetic images (VMIs) at 40 keV. A spectral phantom was scanned using SPCCT and dual-energy CT (EID-DECT) at 8.5 mGy (CTDIvol). 40 keV VMIs...

J. Greffier, R. Grange, D. Dabli et al. · 0 citations
Open access Oct 2026

Assessment of image quality and detectability in computed tomography: Inter‐laboratory comparison of Fourier‐based metrics

Abstract Background The task‐based assessment of image quality in computed tomography (CT) is increasingly used for benchmarking, optimizing acquisition and reconstruction parameters, and predicting observers’ performance. To achieve consistent and reproducible results rely on standardized methodologies and guidelines....

P. Monnin, D. Racine, Luis Ammour et al. · 0 citations
Open access Sep 2026

Size‐specific weighted detectability index for computed tomography image characterization

Task‐based image quality metrics that account for patient‐size variability are needed to characterize reconstructed image performance and support protocol optimization across clinically relevant imaging conditions.

Isabelle Fitton, J. Greffier, D. Dabli et al. · 0 citations
Open access Aug 2026

Ultra-low dose chest-abdomen-pelvis CT with deep-learning image reconstruction for cancer follow-up: Impact on image quality and lesion detection.

PURPOSE The purpose of this study was to compare the image quality and lesion detection between ultra-low dose (ULD) chest-abdomen-pelvis computed tomography (CAP-CT) reconstructed with a deep-learning image reconstruction (DLR) algorithm, and standard-dose CT (STD-CT) in cancer follow-up. MATERIALS AND METHODS A tot...

F. de Oliveira, Sinda Ghabri, Souha Benhalilou et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.