Abstract #2431

Multi-Contrast MRI Reconstruction from Single-Channel Uniformly Undersampled Data via Deep Learning

Christopher Man^1,2, Linfang Xiao^1,2, Yilong Liu^1,2, Vick Lau^1,2, Zheyuan Yi^1,2,3, Alex T. L. Leong^1,2, and Ed X. Wu^1,2

¹Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China, ²Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China, ³Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

This study presents a deep learning based reconstruction for multi-contrast MR data with orthogonal undersampling directions across different contrasts. It enables exploiting the rich structural similarities from multiple contrasts as well as the incoherency arose from complementary sampling. The results show that the proposed method can achieve robust reconstruction for single-channel multi-contrast MR data at R=4.

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

Join Here