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Abstract #2839

Group Sparse Reconstruction of Vector-Valued Images

Joshua Trzasko1, Armando Manduca1

1Mayo Clinic, Rochester, MN, United States

In this work we investigate a generalization of sparsity-driven undersampled image reconstruction strategies for image series which do not have a readily identifiable temporal or parametric sparse transformation but for which strong yet unknown spatiotemporal correlations are anticipated.