Meeting Banner
Abstract #3511

Model-Based Reconstruction for Undersampled High Resolution Diffusion Tensor Imaging Combined with Simultaneous Multi-Slice Acquisitions

Zijing Dong1, Erpeng Dai1, Fuyixue Wang1,2, Yuantao Gu3, Chun Yuan1,4, and Hua Guo1

1Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China, 2Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, United States, 3Department of Electronic Engineering, Tsinghua University, Beijing, People's Republic of China, 4Vascular Imaging Laboratory, Department of Radiology, University of Washington, Seattle, WA, United States

Multi-shot interleaved EPI is an effective method to acquire high-resolution and less distorted diffusion weighted images, but with relatively low acquisition efficiency, especially for diffusion tensor imaging. Here, a novel model-based reconstruction is proposed for accelerated multi-shot diffusion imaging with simultaneous multi-slice (SMS) and partially parallel imaging (PPI). The method can directly estimate diffusion tensors from the undersampled k-space data, by integrating information of all shots and diffusion encoding directions. Simulation and in-vivo experiment demonstrated that the proposed method can achieve higher acceleration efficiency and improved accuracy in tensor estimation compared with conventional 2D GRAPPA.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords