A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360° CZT-camera.

Fiche publication

Date publication

décembre 2025

Journal

EJNMMI research

Auteurs

Membres identifiés du Cancéropôle Est :
Pr MARIE Pierre-Yves

Tous les auteurs :
Bahloul A, Rajadhas F, Doyen M, Lamash Y, Roth N, Roch V, Marie PY, Imbert L

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/41474536

Résumé

Spatial filters are required to suppress the statistical noise of SPECT images but with an unavoidable smoothing effect that further decreases the SUV and contrast. This study assesses a deep-learning noise reduction (DLNR) algorithm, previously developed to further reduce bone SPECT recording time on a high-speed whole-body 360° CZT-camera, when used instead of, rather than in addition to, the conventional spatial filters (CSF) recommended for this camera.