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Abstract #4415

Weighted linear least squares in multi-shell diffusion MRI: Should high b-shells always be weighted less?

Jordan A. Chad1,2 and Ofer Pasternak3
1Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada, 2Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States

Fitting diffusion MRI signal models with the standard weighted linear least squares (WLLS) approach necessarily places lower weight on data with lower SNR, therefore placing lower weight on shells with higher b-values. This can be non-optimal for fitting signal models that rely on information from high b-shells. In this work, we propose a “nested” WLLS approach where each shell is assigned a relative weight, with standard WLLS applied within each shell. We demonstrate that weighting shells equally may be beneficial for fitting signal models dependent on multiple shells.

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