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Abstract #2627


Hamed Y. Mesri 1,2 , Kelvin J. Layton 1,3 , Iven M. Y. Mareels 1 , and Leigh A. Johnston 1,3

1 Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, Victoria, Australia, 2 Victoria Research Laboratory, National ICT Australia, Melbourne, Victoria, Australia, 3 Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia

Cramer Rao Lower Bound analysis is used to evaluate two compartment hindered/restricted diffusion models for estimation of mean axon diameter or axon diameter distributions from diffusion weighted MRI data. Our best-case model analysis demonstrates that the models are prone to high uncertainty levels. In practice, experimental data is acquired in regimes far from best-case model assumptions. Thus estimator performance is necessarily worse than the Cramer Rao error rates, which casts doubt on the ability of these models to robustly estimate microstructural features from diffusion MRI data. The Cramer Rao analysis technique is extensible to all parametric model-based inference methods.

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