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Implementation of a motion compensation system for high resolution brain positron emission tomography Dinelle, Katherine
In this work we implement and validate a compensation method for subject motion occurring during high resolution brain positron emission tomography (PET). Head motion is acknowledged as a significant source of resolution degradation in PET brain imaging; especially at the level of resolution, (2.5 mm)³ , available in the tomograph currently installed at our research centre. Several methods have been developed which are able to partially correct for this motion, however none provide the level of correction accuracy as the method implemented here. An infrared motion tracking system was installed to collect subject motion information during PET scanning. In order to apply these measurements to the PET data, a method for aligning the two reference frames both temporally and spatially was developed. Installation of the motion tracking system allowed an in-depth analysis of typical subject motions encountered during scanning. This permitted us to motivate the need for motion correction, and to identify activities causing head motion which may be limited prior to scanning. Motion corrections based on the acquired data were incorporated into a statistical reconstruction algorithm. First, the position and orientation of each motion impacted event was corrected back to a common reference position. Second, compensation was applied for variations in the relationship between the location of an emission event and the sensitivity of the detectors that measured it due to motion. The consideration of variations in tomograph sensitivity separates this motion correction method from those attempted previously. Experimental validation using phantom data revealed that the motion correction was able to compensate for translations ranging from a few millimeters to a few centimeters. When applied to human data, differences in the quantitative results for images reconstructed with and without motion correction were on the order of those changes we are attempting to study. The motion correction algorithm was developed by a previous student in our group (A. Rahmim), while implementation and testing of the tracking system, and validation of the motion correction algorithm with phantom and human studies was completed as part of this work. Routine application of this motion correction scheme will improve the effective resolution of the tomograph, allowing improved quantification.
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