F-FDG dose reduction using deep learning-based PET reconstruction.
Journal:
EJNMMI research
Published Date:
Jul 1, 2025
Abstract
BACKGROUND: A deep learning-based image reconstruction (DLR) algorithm that can reduce the statistical noise has been developed for PET/CT imaging. It may reduce the administered dose of F-FDG and minimize radiation exposure while maintaining diagnostic quality. This retrospective study evaluated whether the injected F-FDG dose could be reduced by applying DLR to PET images. To this aim, we compared the quantitative image quality metrics and the false-positive rate between DLR with a reduced F-FDG dose and Ordered Subsets Expectation Maximization (OSEM) with a standard dose.
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