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Abstract #4752

An efficient approach for fast signal computation of restricted diffusion with arbitrary gradient waveforms

Diwei Shi1, Sisi Li2, Li Chen1, Quanshui Zheng1, Hua Guo2, and Junzhong Xu3,4,5,6
1Center for Nano and Micro Mechanics, Department of Engineering Mechanics, Tsinghua University, Beijing, China, 2Center for Biomedical Imaging Research, Tsinghua University, Beijing, China, 3Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, 4Vanderbilt University Medical Center, Nashville, TN, United States, 5Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States, 6Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States


Quantitative microstructural imaging based on diffusion MRI usually replies on some simple gradient waveforms, with which analytical expressions can be derived e.g., for fitting cell size. However, it is challenging for this approach for modified irregular gradient waveforms that are increasingly used. Inspired by Callaghan’s matrix formalism, we propose an efficient approach for signal computation with arbitrary gradient waveforms. It can accelerate computation by three orders of magnitude with maintained accuracy, making it feasible in practical data fittings. This work paves the way for quantitative microstructural imaging with arbitrary diffusion gradient waveforms in practice.

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