A comparison of data-driven methods for patient motion estimation in cardiac SPECT imaging

We investigate two data-driven strategies of patient motion estimation in cardiac SPECT imaging. Data-driven methods use the SPECT acquisition data itself to determine motion, with little or no infonnation from external surrogates which track patient motion. In previous work, we investigated a data-driven strategy based on 2D-3D registration using partial reconstruction of the heart and another using maximum-likelihood for simultaneous motion and activity estimation within SPECT reconstruction. In this paper, we compare these strategies using the XCA T phantom made from the MRI studies of volunteers. These XCA T phantoms are based on segmented MRI data by first contouring the body shape, followed by scaling the skeleton to match the volunteer´s skeleton, and then shaping each organ to match the MRI data. This allows modeling of realistic patient motion by replicating the volunteer´s external body motion and internal organ motion. Two datasets were thus obtained: (1) Axial slide and (2) Shoulder twist. Here we present preliminary results for these datasets.