A Novel Spatial-Temporal Adaptive Technique for Reconstruction of Dynamic MRI Series

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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