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- W2082375379 abstract "Fast acquisition of MR images is possible through sparse encoding in the Fourier/Wavelet domain under the incoherentmeasurement constraint required by the theory of compressed sensing (CS) for stable reconstruction. In one such sparseencoding method, we utilize the wavelet tree structure to undersample the wavelet-encoded MRI k-spaces with tailoredspatially-selective RF excitation pulses. The resulting undersampled k-spaces contain many more significant coefficientsthan randomly undersampled k-spaces. Thus, the quality of CS reconstruction based on these undersampled k-spaces isimproved, and such an encoding scheme may reduce the patient scan time for MRI and fMRI. Using a fully sampledFourier encoded 3-D digital brain phantom as the gold standard, a mathematical framework with full-reference andvisual image quality matrices has been proposed to assess the CS reconstruction performance in wavelet-encoded MRI.The quality of MR images recovered from undersampled k-space by different reconstruction methods is computed. Theundersampling rates and noise levels in k-space are considered in evaluating the robustness of CS reconstruction. Thesimulation results show that the performance of CS reconstruction in wavelet-encoded MRI is more accurate and stablethan in Fourier-encoded MRI with the same undersampling rate and noise level, at a significantly reduced scan time." @default.
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- W2082375379 date "2012-02-23" @default.
- W2082375379 modified "2023-09-22" @default.
- W2082375379 title "Quality assessment of fast wavelet-encoded MRI utilizing compressed sensing" @default.
- W2082375379 doi "https://doi.org/10.1117/12.912350" @default.
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