Meeting Banner
Abstract #3422

MR Image Reconstruction from under-sampled measurements using local and global sparse representations

MingJian Hong 1 , MengRan Lin 1 , Feng Liu 2 , and YongXin Ge 1

1 ChongQing University, ChongQing, ChongQing, China, 2 ITEE, The University of Queensland, QLD, Australia

This work presented a new model by enforcing both local and global sparsity, which captures both the patch-level and global sparse structures of the anatomical images. Using a model split approach, the image reconstruction quality can be iteratively further improved. Our simulation results demonstrate that, the proposed method outperform those existing methods using only the patch-level or global sparse structure.

This abstract and the presentation materials are available to members only; a login is required.

Join Here