Meeting Banner
Abstract #1176

Reconstruction of Undersampled Dynamic MRI Data Using Truncated Nuclear Norm Minimization and Sparsity Constraints

Runyu Yang1, Yuze Li1, and Huijun Chen1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China

Achieving high spatio-temporal resolutions is challenging in dynamic magnetic resonance imaging (dMRI). It is effective to use low-rank and sparse jointly for dMRI reconstruction. However, the nuclear norm is usually used as a convex approximation of rank function in many low-rank models, so the result is not optimal. In this study, we proposed a novel method used low rank which utilize a nonconvex norm and sparse jointly for dMRI reconstruction. The effectiveness of the proposed method was investigated in phantom and in-vivo experiments.

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

Join Here