Motion correction of simultaneous brain PET/MR images based on tracer uptake characteristics.
Unlock the power of PET/MR imaging with a novel motion correction method. TCBC leverages tracer uptake patterns to enhance PET-MR alignment, enabling more accurate amyloid burden detection in aging brains.
This study proposes a novel tracer characteristic-based co-registration (TCBC) method to improve the alignment of simultaneous PET/MR images. Compared to conventional mutual information-based approaches, TCBC demonstrated superior accuracy in simulation and real-world data from the OASIS-3 dataset. The improved alignment enabled more robust detection of age-related amyloid burden, with stronger correlations across brain regions. The study's findings highlight the potential of TCBC to enhance PET quantification and support early Alzheimer's disease research, though further validation in larger cohorts is needed to assess its broader applicability.