Abstract #1024
Caveats of non-linear fitting to brain tissue models of diffusion
Ileana O. Jelescu 1 , Jelle Veraart 1 , Els Fieremans 1 , and Dmitry S. Novikov 1
1
Center for Biomedical Imaging, Dept. of
Radiology, NYU Langone Medical Center, New York, New
York, United States
Compared to DTI, white/gray matter models of diffusion
should have improved specificity. However, fit outputs
notoriously suffer from bias and poor precision, with
most models employing simplifying assumptions to
stabilize the fit. Here, we use the example of NODDI to
assess the behavior of nonlinear fitting when all model
parameters are free. We reveal that the typical full
model of brain tissue cannot be reliably determined, due
to a duality of solutions, and to the narrow and shallow
(boomerang-shaped) minimization landscape. Constraining
the fit with fixed parameter values that lack biological
validation is not a trustworthy solution to the problem.
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