Fractional Derivatives for Physicists and Engineers

  • Uchaikin V
ISSN: 1867-8440
N/ACitations
Citations of this article
64Readers
Mendeley users who have this article in their library.

Abstract

We present a novel interpretation of non-monoexponential diffusion-weighted signal decay with b-value in terms of the theory of anomalous diffusion. Anomalous diffusion is the theory of diffusing particles in environments that are not locally homogeneous, such as brain tissue. In such environments the model of restricted diffusion commonly employed in the analysis of diffusion MR data is not valid, leading to a nonlinear time dependence for the mean-squared displacement of spins, and to a prediction of a stretched exponential form for the signal decay. We show that this prediction leads directly to a new parameter, the anomalous exponent, which may be measured from scan data and from this we can estimate a fractal dimension, dw, which categorizes the complexity of the excursions of diffusing spins. We construct images of the anomalous exponent and fractal dimension from in vivo human brain data. Distributions of exponents and dimensions are constructed in grey and white matter and cerebrospinal fluid. We observe that these distributions peak at biologically plausible values consistent with previous studies: grey matter dw = 2.366 ± 0.31, white matter dw = 2.587 ± 0.39, CSF dw = 1.970 (mode). Marked contrast is observed between grey and white matter when compared with lateral ventricle CSF. We then consider the anisotropy of the value of the anomalous exponent and define quantities analogous to the mean diffusivity and fractional anisotropy that are commonly generated from diffusion tensor images. Magn Reson Med, 2008. © 2008 Wiley-Liss, Inc.

Author supplied keywords

Cite

CITATION STYLE

APA

Uchaikin, V. V. (2013). Fractional Derivatives for Physicists and Engineers. Chaos: An Interdisciplinary Journal of Nonlinear Science (Vol. 27, p. xvi+504). Springer Berlin Heidelberg. Retrieved from http://dx.doi.org/10.1007/978-3-642-33911-0 http://dx.doi.org/10.1007/978-1-4471-2233-3

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free