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Abstract #3642

Computing the Orientational-Average of Diffusion-Weighted MRI Signals: A Comparison of Different Techniques

Maryam Afzali1, Hans Knutsson2,3, Evren Özarslan2,3,4, and Derek K Jones1,5
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, 2Department of Biomedical Engineering, Linköping University, Linköping, Sweden, 3Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden, 4These authors share last authorship, Linköping, Sweden, 5These authors share last authorship, Cardiff, United Kingdom

Numerous applications in diffusion MRI involve computing the orientationally-averaged diffusion-weighted signal. Most approaches assume that the gradient vectors are uniformly distributed on a sphere, computing the orientationally-averaged signal through arithmetic averaging. One challenge is that not all acquisition schemes have gradient vectors distributed over perfect spheres. Alternative averaging methods include: weighted signal averaging; spherical harmonic; and Mean Apparent Propagator MRI (MAP-MRI). Here, these methods are compared under different signal-to-noise (SNR) realizations. With dense and isotropically-distributed sampling, all methods give comparable results. As the SNR and number of data points are reduced, MAP-MRI-based approaches give pronounced improvements over the other methods.

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