Undersampled dynamic magnetic resonance imaging using patch-based spatiotemporal dictionaries

Dynamic magnetic resonance imaging (dMRI) requires high spatial and temporal resolutions, which is challenging due to the low imaging speed. To reduce the imaging time, a patch-based spatiotemporal dictionary learning (DL) model is proposed for compressed-sensing reconstruction of dynamic images from undersampled data. Specifically, the dynamic image… CONTINUE READING

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Averaging 7 citations per year over the last 3 years.

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