Marker-less multi-frame motion tracking and compensation in PET-brain imaging

Abstract

In PET brain imaging, patient motion can contribute significantly to the degradation of image quality potentially leading to diagnostic and therapeutic problems. To mitigate the image artifacts resulting from patient motion, motion must be detected and tracked then provided to a motion correction algorithm. Existing techniques to track patient motion fall into one of two categories: 1) image-derived approaches and 2) external motion tracking (EMT). Typical EMT requires patients to have markers in a known pattern on a rigid too attached to their head, which are then tracked by expensive and bulky motion tracking camera systems or stereo cameras. This has made marker-based EMT unattractive for routine clinical application. Our main contributions are the development of a marker-less motion tracking system that uses lowcost, small depth-sensing cameras which can be installed in the bore of the imaging system. Our motion tracking system does not require anything to be attached to the patient and can track the rigid transformation (6-degrees of freedom) of the patient’s head at a rate 60 Hz. We show that our method can not only be used in with Multi-frame Acquisition (MAF) PET motion correction, but precise timing can be employed to determine only the necessary frames needed for correction. This can speeds up reconstruction by eliminating the unnecessary subdivision of frames.