A Novel Spatial-Temporal Adaptive Technique for Reconstruction of Dynamic MRI Series
Julia V Velikina 1 and Alexey A Samsonov 2
University of Wisconsin - Madison, Madison,
Wisconsin, United States,
of Wisconsin - Madison, WI, United States
A novel method is proposed for image series
reconstruction from incomplete data that improves
performance of techniques relying on temporal basis
representation for dimensionality reduction. The
improvement is achieved by automated iterative partition
of FOV into several clusters with similar temporal
dynamics and choosing a different locally adapted basis
for each cluster. The spatially adaptive reconstruction
allows for better image representation and higher SNR.
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