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Abstract #1512

Strategies for Compensating for Missing k-space Data in a Novel Half-Fourier Reconstruction

Seul Lee1 and Gary Glover2

1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States

Functional MRI (fMRI) is sensitive to off-resonance from air-tissue susceptibility interfaces. Existing half-Fourier reconstruction is vulnerable to off-resonance since it may lose most of the image energy (near k=0) with a large amount of off-resonance. In a previous study, we suggested a new half Fourier (even/odd (E/O)) reconstruction and showed it was more robust to off-resonance compared to Homodyne reconstruction. E/O reconstruction acquires every other line in k-space. Therefore, neighboring data can be used to compensate for the missing data. In this study, we suggest several strategies for compensating for missing k-space data in kx-ky as well as kz direction.

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