A major limitation of high-resolution positron-emission-tomography (PET) are subject movements during acquisition. We propose a new motion compensation algorithm called "Blind Motion Compensated Reconstruction" (BMCR) that is able to deal with frames of extremely low statistics in the case of smooth motion. BMCR reconstructs both image and rigid motion just from the recorded data and does not need external motion tracking. BMCR consists of an optimization framework in which a pair of image and motion that leads to the minimal value of an objective function is sought. Results show that BMCR is even comparable to state-of-art reconstruction of motion-free data.     «

A major limitation of high-resolution positron-emission-tomography (PET) are subject movements during acquisition. We propose a new motion compensation algorithm called "Blind Motion Compensated Reconstruction" (BMCR) that is able to deal with frames of extremely low statistics in the case of smooth motion. BMCR reconstructs both image and rigid motion just from the recorded data and does not need external motion tracking. BMCR consists of an optimization framework in which a pair of image...     »