Validation of a data-driven motion-compensated PET brain image reconstruction algorithm in clinical patients using four radiotracers

• Published in: EJNMMI physics Vol. 12; no. 1; pp. 11 - 15
• Main Authors: Munk, Ole L., Rodell, Anders B., Danielsen, Patricia B., Madsen, Josefine R., Sørensen, Mie T., Okkels, Niels, Horsager, Jacob, Andersen, Katrine B., Borghammer, Per, Aanerud, Joel, Jones, Judson, Hong, Inki, Zuehlsdorff, Sven
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 03.02.2025; Springer Nature B.V; SpringerOpen
• Subjects: Algorithms; Applied and Technical Physics; Brain; Brain research; Computational Mathematics and Numerical Analysis; Data driven; Dementia; Diagnostic systems; Engineering; Fluorine isotopes; Head movement; Image degradation; Image quality; Image reconstruction; Imaging; Medical imaging; Medicine; Medicine & Public Health; Motion compensation; Motion correction; Neuroimaging; Nuclear Medicine; Original Research; PET; Positron emission; Radioactive tracers; Radiology; Reconstruction; Rigid structures; Translations; Motion correction; Reconstruction; Brain; Data driven; PET; Dementia

Purpose Patients with dementia symptoms often struggle to limit movements during PET examinations, necessitating motion compensation in brain PET imaging to ensure the high image quality needed for diagnostic accuracy. This study validates a data-driven motion-compensated (MoCo) PET brain image reco...