Direct list mode reconstruction for motion compensation

As resolution of PET increases, subject movement is becoming a significant factor that limits image quality. It is important to develop image reconstruction methods that can compensate motion. The basic approach that we have taken in this work is to use video cameras to track the subject movement and to use this information in reconstruction algorithms. We have developed a direct list-mode reconstruction algorithm that incorporates the subject motion information in the likelihood function. The method can accurately compensate measured motion and it does not require interpolation of either measured events or reconstructed images. We applied the method to experimental data from a phantom in a microPET scanner.