Meeting Banner
Abstract #4186

Dynamic MRI Reconstruction of the Whole Liver with High Acceleration using Low Rank Tensor and Weighted Group Sparsity

Bei Liu1, Huajun She1, Yufei Zhang1, Zekang Ding1, Zhijun Wang1, and Yiping P. Du1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China


We propose an algorithm for dMRI reconstruction from highly under-sampled k-space data acquired during free breathing. Stack-of-star GRE radial sequence with self-navigator is used to acquire the data. We explore spatial and temporal redundancy for the reconstruction by using weighted group sparsity, weighted sparsity, and low-rank tensor. Additionally, a tensor total variation is used to ensure spatial and temporal smoothness. By applying a weighting function to the sparsity and group sparsity, the subtle structural sparsity features in the sparse domain can be better utilized. The proposed algorithm has the potential to be used in clinical applications such as MR-guided surgery.

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

Join Here