Invention of diffusion imaging has empowered the neuro-scientists with maps of microscopic
structural information that could be taken in vivo. Different diffusion models have been proposed since the
inception of the diffusion tensor imaging. Diffusion models have been mainly used for visualizing the brain
tissues as precise as possible. However, information about underlying structure of the fiber structures is required
for developing precise biomarkers for diseases. The present research aims reviewing diffusion models
based on their ability in determining fibers’ underlying structure and how these models could be improved. Diffusion
modelling methods will be categorized, based on how they model the diffusion, into two main categories namely parametric
and non-parametric methods. It will be discussed how modelling assumptions and other strategies could help in developing
precise biomarkers. Furthermore, different biomarkers that have been proposed for determining common pathologies
of neurodegenerative diseases will be briefly reviewed.
Keywords: Anisotropic measures, biomarkers, diffusion models, infertility, neurodegenerative diseases.
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