A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360° CZT-camera
A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360° CZT-camera
F. Rajadhas, L. Imbert, Achraf Bahloul, Matthieu Doyen et al.
Journal
EJNMMI Research
Topics
Medical Imaging Techniques and Applications
article
A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360° CZT-camera
F. Rajadhas, L. Imbert, Achraf Bahloul, Matthieu Doyen, Yechiel Lamash, Véronique Roch, Nathaniel Roth, Pierre-Yves Marie
article en
Abstract
No abstract available for this paper.
Publication Tag
EJNMMI ResearchVol. 16(1)
Institutions
Inserm (FR), Centre d’Investigation Clinique Innovation Technologique de Nancy (FR), Imagerie Adaptative Diagnostique et Interventionnelle (FR), Université de Lorraine (FR)