Recent progresses of accelerated MRI using annihilating filter-based low-rank interpolation

Kyong Hwan Jin, Dongwook Lee, Juyoung Lee, Jong Chul Ye

Abstract: Recently, an annihilating filter based low-rank Hankel matrix approach (ALOHA) was proposed as a general framework for sparsity-driven k-space interpolation method for compressed sensing MRI (CS-MRI). The principle of ALOHA framework is based on the fundamental duality between the transform domain sparsity in the primary space and the low-rankness of weighted Hankel matrix in Fourier domain, which converts CS-MRI to a k-space interpolation problem using structured matrix completion. In this review, we explain the theory behind ALOHA. Experimental results with in vivo data for multi-coil dynamic imaging, parametric mapping as well as Nyquist ghost correction confirmed that the proposed method has potential to be a general solution of various MR imaging problems.