Deep learning‐based T1‐enhanced selection of linear attenuation coefficients (DL‐TESLA) for PET/MR attenuation correction in dementia neuroimaging

Abstract

The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of correlation between MR signal and tissue electron density. Based on our finding that longitudinal relaxation rate, or R1, is associated with CT Hounsfield unit in bone and soft tissues in the brain, we propose a deep learning T1‐enhanced selection of linear attenuation coefficients (DL‐TESLA) method to incorporate quantitative R1 for PET/MR AC and evaluate its accuracy and longitudinal test–retest repeatability in brain PET/MR imaging.