Optimizing motion correction in reconstruction of respiratory-gated spect
Respiratory-gated acquisition with amplitude binning in cardiac SPECT can reduce the extent of motion blur, but the acquired data can exhibit high variability among both gate intervals and acquisition angles. We investigate whether we can improve the reconstruction accuracy by optimizing the motion correction among respiratory gates in the presence of such variability. To account for the differing noise characteristics among respiratory gates, we develop a joint motion-estimation and image-reconstruction approach, in which the respiratory motion is estimated simultaneously along with the source distribution. In the experiments, we demonstrated this joint estimation-reconstruction approach with both quantitative simulated NCAT data and a set of clinical acquisition. We also explored its robustness with reduced imaging dose. The results show that the proposed approach can further improve the reconstructed myocardium over a pre-reconstruction motion-estimation approach.