Abstract #2627
PERFORMANCE BOUNDS FOR DIFFUSION MRI MODELS OF TISSUE MICROSTRUCTURE
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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