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Abstract #2405

Fast, Variable System Delay Correction for Spiral Trajectories

Payal Sharad Bhavsar1, Nicholas Ryan Zwart1, James Grant Pipe1

1Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, United States

Spiral encoding methods may exhibit image artifacts due to system delays and eddy current. This papers extends a previous approach to estimate time-varying system delays for stack-of-spirals based trajectories, reducing the computational time by a factor of 30. The proposed method is very fast, easy to implement, includes gradient coupling effects, is robust to off-resonance, and estimates delays for each gradient channel over the data acquisition time.

Keywords

abstract accuracy acquisition alley allowed almost appear applied artifacts axial axis barrow channel coil coils collected compensated computational constant continuous correction correlation corresponds coupling cylinders dashed delay delays density dependent eddy eight either eliminated entire estimating except excite exhibit experiment extends external fast gradient grant grid gridded hardware head illustrates imperfections improvement includes initial institute interleaves intersecting length maps measure minute neurological noise object onto orthogonal orthogonally overlapping part performance period phantom phoenix pipe previous proposed quality quickly reconstructed reduce reduced reduction relatively require requires resolution robust sampled sampling scanner separate sets shading simple simulated simulations slice slices slightly space spiral spirals stack substantially synthesized system trajectories trajectory uncorrected validate variable varying volume volumes windowed