Motion Management in Positron Emission Tomography/Computed Tomography and Positron Emission Tomography/Magnetic Resonance.
Authors
Affiliations (3)
Affiliations (3)
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
- Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Radiology and Biomedical Imaging, Yale University, New Haven, CT 06520, USA. Electronic address: [email protected].
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, Leon and Norma Hess Center for Science and Medicine, 1470 Madison Avenue 1st Floor, New York, NY 10029, USA. Electronic address: [email protected].
Abstract
Motion in clinical positron emission tomography (PET) examinations degrades image quality and quantification, requiring tailored correction strategies. Recent advancements integrate external devices and/or data-driven motion tracking with image registration and motion modeling, particularly deep learning-based methods, to address complex motion scenarios. The development of total-body PET systems with long axial field-of-view enables advanced motion correction by leveraging extended coverage and continuous acquisition. These innovations enhance the accuracy of motion estimation and correction across various clinical applications, improve quantitative reliability in static and dynamic imaging, and enable more precise assessments in oncology, neurology, and cardiovascular PET studies.