Meeting Banner
Abstract #0130

Calibrationless Chemical Shift Encoded Imaging Using a Time-Segmented K-Space Reconstruction

Samir D. Sharma1, 2, Joshua D. Trzasko3, Armando Manduca3

1Radiology, University of Wisconsin - Madison, Madison, WI, United States; 2Electrical Engineering, University of Southern California, Los Angeles, CA, United States; 3Mayo Clinic, Rochester, MN, United States

Conventional image-domain-based methods for chemical shift encoding are limited both by their long scan time, which can restrict spatial resolution and/or volume coverage, and their sensitivity to intraecho off-resonance, which can cause geometric distortion. Previous works have proposed either accelerating image-domain-based methods or using a k-space-based formulation to mitigate the effects of intraecho off-resonance. In this work, we develop and demonstrate a framework for accelerated k-space-based chemical shift encoding. We employ a time-segmented approximation of the multispecies MR signal equation and we exploit prior information on intercoil structure and image sparsity to achieve acceleration. We demonstrate accelerated water-fat separation with reduced geometric distortions as compared to a conventional image-domain-based method.

Abstract PDF Presentation Video

Keywords

accelerated accelerating acceleration achieve acknowledge acquisition addition advanced aligned alternating amplitude approximation array arrows audience avoid avoiding axis bandwidth cause channel chemical circle clear clinic clinical coefficients coils column compact composed coverage cubic dashed dense develop developed disk distortion distortions domain dropout either electrical employ employs encode encoded encoding engineering estimation exploiting exploits exponential field finer formulation framework frequency fully function future generated geometric highlight ideal implement index iterative jointly least length limited local long matrices mayo minimization mitigate model modeled modeling note object operate pattern peak penalized pileup pixels position prior promotes proposed proven radiology rank readout receiver reconstructed reconstruction reduced reeder regression represent represents residual resolution restrictions retrospectively sample sampled sampling scale scanner segment segmented segments sensing sensitivity separation settings simulate slices southern space sparsity spatial spatially species specifically spectral splines squares step structure successively support swaps target thank thigh tool update volume water wavelet white window wish yields