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Abstract #4459

T1 mapping with golden-angle radial sampling: A comparison of direct and indirect reconstruction

Nikolaos Kallistis1, Ian Rowe1, and Steven Sourbron2

1Leeds Institute of Biomedical and Clinical Sciences, University of Leeds, Leeds, United Kingdom, 2Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom

The purpose of the study is to compare a direct model-based reconstruction with an indirect compress sensing reconstruction for the estimation of T1-map, from simulated radial sampled datasets. Comparisons are performed for the binning strategy that is optimal in each case as measured by T1-errors.

The direct reconstruction solves the nonlinear-least-squares optimization problem with a gradient-based L-BFGS algorithm without regularization, while for the indirect method the images are reconstructed using the iGRASP technique.

The accuracy for both methods is similar, however the computational time of the model-based reconstruction is a limiting factor for clinical applications.

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