This paper presents a multi-scale low rank based method to implement cardiac MR(Magnetic Resonance) image reconstruction

which represented a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes.And the sum of block-wise low rank matrices was used as a constraint to approach the MR image reconstruction.Two different cardiac MR datasets were used to evaluate the performance of the proposed method.Compared with the state-of-art methods

such as the

k-t

SLR(

k-t

Sparsity Low Rank) method and L+S (Low rank plus Sparse) method

the proposed MSL method can offer improved reconstruction solution in terms of higher signal to error ratio and better structural simil

arity index

but with longer reconstruction time.