Yihuan Lu, PhD, Associate Research Scientist, Yale University PET Center, and John Onofrey, PhD, Assistant Professor of Radiology and Biomedical Imaging and of Urology, have been awarded an R21 grant from the National Institutes of Health (NIH) to develop “Data-Driven Head Motion Correction In PET Imaging Using Deep Learning.” Positron-emission tomography (PET) imaging of the brain is a highly useful tool for biomedical research and clinical practice. However, head motion during scanning degrades PET image quality and introduces image artifacts. To address these challenges, Drs. Lu and Onofrey plan to develop a data-driven methodology using deep learning to track and estimate rigid head motion using PET raw data. Both tracer type and time will be incorporated as conditional variables into this deep neural network design in order to handle diverse PET tracer types and their dynamic behavior.
Submitted by Angel Machon on May 04, 2020