Respiratory motion correction utilizing geometric sensitivity in 3D PET: A simulation study

The PET image quality can be degraded due to respiratory motion. In this paper, we present a new data-driven method for respiratory motion compensation that utilizes the geometric sensitivity feature of a 3D-PET scanner system operating in list event acquisition mode. The count rate from a given organ will depend on the axial location of the organ due to the geometric sensitivity. As a result the respiratory transforms to the reference frame can be determined from count rate changes which are determined to suitable temporal resolution from the list-mode data stream. This method only uses LOR events and is non-invasive, no additional hardware device systems are required and there is no additional preparation required. Simulation results demonstrate that the geometric sensitivity correction (GSC) method may reduce motion degradation.