Abstract #1256

Field-Correcting GRAPPA (FCG) for improved mitigation of even-odd and field-related artifacts in EPI

Nan Wang¹, Daniel Abraham², Adam B Kerr^2,3, Hua Wu³, Congyu Liao¹, Xiaozhi Cao¹, Jonathan R Polimeni^4,5,6, Renzo Huber⁷, and Kawin Setsompop¹

¹Radiology Department, Stanford University, Stanford, CA, United States, ²Electrical Engineering, Stanford University, Stanford, CA, United States, ³Cognitive and Neurobiological Imaging Center, Stanford University, Stanford, CA, United States, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁵Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁶Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States, ⁷Functional Magnetic Resonance Facility (FMRIF), National Institutes of Health, Bethesda, MD, United States

Synopsis

Keywords: Artifacts, Artifacts

Motivation: Field perturbation from gradient error and eddy current has been a long-standing issue for EPI, especially with high gradient performance or ramp sampling

Goal(s): To develop a MLP based Field-Correcting GRAPPA (FCG) that accounts for spatial-varying field and produces artifacts-mitigated images

Approach: Calibration data with dual polarity were acquired. A MLP based kernel was trained to take single-polarity data as input and output the clean averaged data. It was applied for both phantom and in vivo undersampled EPI with ramp-sampling.

Results: FCG produced best correction results for ramp-sampling EPI, with potentials for wide applications including fMRI.

Impact: A Field-Correcting GRAPPA (FCG) technique was developed to correct the field perturbation induced image artifacts for EPI, which accounts for spatial varying field and produced promising resulting on ramp-sampling cases, with great potentials for wide applications including fMRI.

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