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Abstract #2447

A ­Partial-Fourier Method Recovering Signal Loss from Off-resonance

Seul Lee1, Haisam Islam2, and Gary Glover3

1Department of Electrical Engineering, Stanford University, Stanford, CA, United States, 2Department of Bioengineering, Stanford University, Stanford, CA, United States, 3Department of Radiology, Stanford University, Stanford, CA, United States

Functional MRI (fMRI) can have signal dropout due to off-resonance at susceptibility interfaces between air and tissue. Partial Fourier reconstruction is used for fMRI since it reduces scan time, however, existing partial Fourier reconstruction is vulnerable to off-resonance. In a previous study, we introduced a new partial Fourier reconstruction (even/odd (E/O)) and showed the new method was more robust to off-resonance compared to homodyne through simulation from fully sampled data. In this study, we acquired subsampled hypercapnia task fMRI data using both homodyne and E/O and showed there is less signal dropout and higher activation with E/O.

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