A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET

202175 citationsJournal Articlehybrid Open Access

Authors

Song Xue · University of Bern

Rui Guo · Ruijin Hospital

Karl Peter Bohn · University of Bern

Jared Matzke · Technical University of Munich

Marco Viscione · University of Bern

Ian Alberts · University of Bern

Hongping Meng · Shanghai Jiao Tong University

Abstract

The deep learning development for extensible application on unknown scanners and tracers may improve the trustworthiness and clinical acceptability of AI-based dose reduction.

Topics & Keywords

Medical Imaging Techniques and Applications Radiomics and Machine Learning in Medical Imaging Advanced X-ray and CT Imaging

Publication Details

Published in: European Journal of Nuclear Medicine and Molecular Imaging

Volume 49, Issue 6, pp. 1843-1856

DOI: 10.1007/s00259-021-05644-1

Field-Weighted Citation Impact: 7.91

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A cross-scanner and cross-tracer deep learning method for the recovery of standard-dose imaging quality from low-dose PET

Authors

Abstract

Topics & Keywords

Publication Details