Projection geometry invariant nonrigid motion correction

Various functional imaging cameras are specialized to acquire the biochemical processes in a time and space-dependent way of different organs in-vivo. The main properties of functional imaging are relatively low resolution and high sensitivity to be manifested in multiple collimation and detection strategies. As a result, the projection geometry in each multi-vendor camera has large variability, making the inherent and acquired imaging artifacts hard to handle by algorithms. A theoretical methodology is developed to overcome one of the biggest effects of acquired imperfection, the patient’s motion which interferes with the heart’s motion. It is well known that, the different motion influences may alter the crucial quantitative measures. These are rendered as the main important issues of functional imaging. Solutions exist by multiple commercial approaches already, but only for specific collimation geometries. This motivation inspired the development of an automatic optimization method to overcome the above-mentioned motion artifact with general collimation geometry on the complete detector field-of-view (FOV). The theory (geo mc) is based on a metamorphic control problem with Optimal Transport (OT) augmentation to overcome the problems introduced by the acquired artifacts and intrinsic imaging system. The algorithm is designed on multi-pinhole (MPH) and low energy high resolution (LEHR) collimation with promising a great improvement over Optial Flow (OF) methods. The aim is to further lower the error in total perfusion deficit (TPD) scores for practical ability to apply on the patient Single-Photon Emission Computed Tomography (SPECT) studies as well. Conclusion: A geometry invariant global optimization technique with nonrigid displacement correction is shown and designed on multiple projection acquisitions. Further application on phantom studies and later patient applicability looks promising for 4 dimensional protocols too.