Head motion during brain PET imaging is not uncommon and can negatively affect image quality. Motion correction techniques typically either use hardware to prospectively measure head motion, or they divide the acquisition into short fixed-frames and then align and combine these to produce a motion free image. The aim of this work was to retrospectively detect when motion occurred in PET data without the use of motion detection hardware, and then align the frames defined by these motion occurrences. We describe two methods that use either principal component analysis or the motion induced spatial displacements over time to detect motion in raw time-of-flight PET data.

 

(후략)