Meeting Banner
Abstract #1981

Kernel-based Fast EPTI Reconstruction with Neural Network

Muheng Li1, Jie Xiang2, Fuyixue Wang3,4, Zijing Dong3,5, and Kui Ying2
1Department of Automation, Tsinghua University, Beijing, China, 2Department of Engineering Phycics, Tsinghua University, Beijing, China, 3A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, 4Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, United States, 5Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA, United States

A machine learning based reconstruction framework for Echo Planar Time-resolved Imaging(EPTI) is proposed. This work utilized the special data acquisition trajectory of EPTI, a highly-accelerated spatiotemporal CAIPI sampling, to divide the k-space recovery task into a multi-process program. The missing data is filled within an indicated small kernel with a fully connected neural network. Through image reconstruction tests on human brain data set acquired by EPTI, we demonstrated the high efficiency of this algorithm by shortening the reconstruction time of 216×216×48×32 k-data from over 10 minutes to about 20 seconds.

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

Join Here