Abstract #3451

A Subspace EPTI Reconstruction with Magnitude-only Bases and Synergistic Phase Bias Updating for Distortion-Free Diffusion-Relaxometry MRI

Erpeng Dai¹, Zijing Dong^2,3, Kawin Setsompop^1,4, and Jennifer A McNab¹

¹Departmnet of Radiology, Stanford University, Stanford, CA, United States, ²Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ³Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁴Departmnet of Electrical Engineering, Stanford University, Stanford, CA, United States

Synopsis

The distortion-free diffusion and relaxometry images provided by echo-planar time resolved imaging (EPTI) ) represent a valuable acquisition strategy for mapping brain tissue microstructure. However, given the large under-sampling factor of EPTI acquisition and the intrinsically low SNR of diffusion MRI, an SNR-efficient reconstruction is vital. Subspace reconstruction can improve SNR efficiency by reducing the number of unknowns. In subspace reconstruction, the selection of bases strongly affects the reconstruction image fidelity, SNR, and computational efficiency. Here, we explore a new subspace-based EPTI reconstruction with magnitude-only bases and synergistic phase bias updating and demonstrate its performance for microstructural mapping.

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