Figure 1

Reconstruction framework for dual-slice k-t imaging. The training data is unfolded prior to reconstruction yielding the training matrix term (M) in the reconstruction. Undersampled data is unfolded point-wise in x-f space using a similar approach as in single slice k-t SENSE, however solving for two slices simultaneously. S is the encoding matrix (including sensitivities), ρ the unfolded, ρ _alias the folded pixels and σ² the noise covariance matrix. The square brackets show the variables dimensions per unfolded pixels (R: undersampling factor, C: number of coils).