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NIRS-SPM

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k-t FOCUSS

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Compressive MUSIC

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Super-resolution Microscopy

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Patch Low Rank MRI

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Sparse SPM

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ALOHA Inpainting

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ALOHA for MRI

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Annihilating Filter-based Low-Rank Hankel Matrix (ALOHA) for MR reconstruction

Related publications

1. Kyong Hwan Jin, Dongwook Lee, and Jong Chul Ye. "A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank hankel matrix,"  IEEE Trans. on Computational Imaging, vol 2, no. 4, pp. 480 - 495, Dec.  2016.
2. Jong Chul Ye, Jong Min Kim, Kyong Hwan Jin and Kiryung Lee, "Compressive sampling using annihilating filter-based low-rank interpolation",  IEEE Trans. on Information Theory, 2016 (in press).
3. Kyong Hwan Jin, Ji-Yong Um, Dongwook Lee, Juyoung Lee, Sung-Hong Park and Jong Chul Ye,  " MRI artifact correction using sparse + low-rank decomposition of annihilating lter-based Hankel matrix", Magnetic Resonance in Medicine (in press),  2016
4. Juyoung Lee, Kyong Hwan Jin, and Jong Chul Ye, "Reference-free single-pass EPI Nyquist ghost correction using annihilating filter-based low rank Hankel  matrix (ALOHA)", Magnetic Resonance in Medicine, 10.1002/mrm.26077, Feb. 17, 2016.
5. Dongwook Lee,, Kyong Hwan Jin, Eung Yeop Kim, Sung-Hong Park and Jong Chul Ye, "Acceleration of MR parameter mapping using annihilating filter-based low rank Hankel matrix (ALOHA)", Magnetic Resonance in Medicine, 10.1002/mrm.26081, Jan. 1, 2016.​

   Abstract—Parallel MRI (pMRI) and compressed sensing MRI (CS-MRI) have been considered as two distinct reconstruction problems. Inspired by recent k-space interpolation methods, an annihilating filter-based low-rank Hankel matrix approach is proposed as a general framework for sparsity-driven k-space interpolation method which unifies pMRI and CS-MRI. Specifically, our framework is based on a novel observation that the transform domain sparsity in the primary space implies the low-rankness of weighted Hankel matrix in the reciprocal space. This converts pMRI and CS-MRI to a k-space interpolation problem using a structured matrix completion. Experimental results using in vivo data for single/multicoil imaging as well as dynamic imaging confirmed that the proposed method outperforms the state-of-the-art pMRI and CS-MRI.

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