Our brain manifests an inherent structural complexity that can be captured by fractal geometry – a framework able to represent objects that show self-similarity in a proper range of spatial scales. The fractal dimension is the most popular index of fractal geometry and represents how much a structure fills the space. In this presentation, we will introduce the basics of fractal geometry and show, using magnetic resonance (MR) imaging, that both the cerebral cortex and white matter are natural fractals in a proper range of spatial scales. We will discuss the potential of the fractal dimension as neuroimaging marker of the complexity of the cerebral cortex and white matter. Moreover, the role of the fractal dimension as a candidate marker to assess cerebral changes in brain development, normal aging, and various neurodegenerative and cerebrovascular disorders will be discussed. Clinical applications of the fractal dimension using machine learning systems and findings from MR images acquired at ultra-high magnetic field (7 T) will also be covered.
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