Respiratory motion during PET/CT imaging is a matter of concern due to degraded image quality and reduced quantitative accuracy caused by motion artifacts. One class of motion correction methods relies on hardware-based respiratory motion tracking systems in order to use respiratory cycles for correcting motion artifacts. Another class of hardware-free methods extract motion information from the reconstructed images or sinograms. Hardware-based methods, however, are limited by calibration requirement, patient discomfort, lack of adaptability during scanning, presence of electronic drift during respiratory monitoring etc. Extracting motion information from reconstructed images is also limited by the fact that the original raw information requires significant processing before it can be used. Hence the motivation behind this work is to introduce a software-based approach that can be applied on raw 64-bit listmode data. The basic design of the proposed method is based on the fundamentals of Positron Emission Particle Tracking (PEPT) with additional incorporation of Time of Flight (TOF) information. Respiratory motion of patients has been extracted from the raw PET data by tracking a point source attached to the patient in areas on and near the chest. The key objective of this work is to describe a new process by which this particle tracking based motion correction system can eventually be lesion specific and correct the motion for a particular lesion within the patient. This work thus serves as a framework for lesion specific motion correction.

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http://dx.doi.org/10.1109/EMBC.2018.8513486DOI Listing

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