PURPOSE: Patient motion during a positron emission tomography (PET) scan can lead to significant resolution loss. Two of the main motion correction techniques employed to ameliorate the loss of image quality due to respiratory motion in the torso are postreconstruction registration (PRR) and motion-compensated image reconstruction (MCIR). In this study, the authors investigated whether versions of these methods that utilize registration-based weighting of the constituent respiratory gated data offer any advantage over the standard versions that use equal weighting. The registration-based weights were designed to penalize gates that were poorly registered to the reference gate. METHODS: SimSET was used to simulate data from the NCAT phantom with six lesions added in the lung and liver. Images were reconstructed using registration-weighted PRR and MCIR algorithms, where the registration weighting was based on the mutual information (MI) of each registered gate and the reference gate. More specifically, relative to equal weighting, for which the weight for each gate is the inverse of the number of gates, the weights were increased for MI greater than the average MI and reduced for gates with MI less than the average MI. A scale factor was used to increase the range of the weights, and PRR and MCIR images were produced for a range of scale factor values. RESULTS: At the optimal values of the scale factor, registration-weighted PRR produced significantly higher contrast-to-noise ratio (CNR) for each lesion than PRR (p
