Abstract #3710

A Fast Reconstruction Algorithm for Accelerated Multi-Contrast MRI

Itthi Chatnuntawech ¹ , Berkin Bilgic ² , Adrian Martin ^1,3 , Kawin Setsompop ^2,4 , and Elfar Adalsteinsson ^1,5

¹ MIT, Cambridge, MA, United States, ² A. A. Martinos Center for Biomedical Imaging, MA, United States, ³ Universidad Rey Juan Carlos, Mostoles, Madrid, Spain, ⁴ Harvard Medical School, MA, United States, ⁵ Harvard-MIT Heath Sciences and Technology, MA, United States

We present an efficient algorithm to jointly reconstruct a set of images with different contrasts that has faster reconstruction time and better quality as measured by the normalized root-mean-square error (RMSE). To efficiently solve the lower case Greek iota

_2,1 -regularized optimization problem, our proposed algorithm first adopts the Split-Bregman (SB) technique to break down the problem into sub-problems. We efficiently compute a closed-form solution to each of the sub-problems with the help of a finite difference operator in k-space. The proposed algorithm (SB-L21) offers up to 32x faster reconstruction with up to 30% reduction in an average RMSE of the reconstructed images across all contrasts and slices, compared to other methods, including M-FOCUSS and SparseMRI.

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