Keywords: Sparse & Low-Rank Models, Image Reconstruction, EPTI
Motivation: Subspace reconstruction is widely used in MRI reconstruction, but the selection and impact of bases need further analysis.
Goal(s): We want to evaluate the influence of bases obtained by different methods on subspace reconstruction.
Approach: We generated different bases from Bloch simulation and calibration scan on healthy subjects and brain tumor subjects and evaluate the subspace reconstruction results with GESE-EPTI data.
Results: Subspace bases from calibration scan can optimize the reconstructed results without increasing scan time. The bases from brain tumor subjects and healthy subjects are evaluated and indicate consistent results. Besides, linear transformations can optimize results without the need for reconstruction.
Impact: We evaluate the subspace bases from Bloch simulation and calibration scan in MRI subspace reconstruction and demonstrate bases from calibration scan can optimize the reconstructed results. Subspace reconstruction results were consistent by bases from brain tumor and healthy subjects.
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