Fractals in neuroimaging

Salim Lahmiri, Mounir Boukadoum, Antonio Di Ieva

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Several natural phenomena can be described by studying their statistical scaling patterns, hence leading to simple geometrical interpretation. In this regard, fractal geometry is a powerful tool to describe the irregular or fragmented shape of natural features, using spatial or time-domain statistical scaling laws (power-law behavior) to characterize real-world physical systems. This chapter presents some recent works on the usefulness of fractal features, mainly the fractal dimension and the related Hurst exponent, in the characterization and identification of pathologies and radiological features in neuroimaging.
Original languageEnglish
Title of host publicationThe Fractal geometry of the brain
EditorsAntonio Di Ieva
Place of PublicationNew York
PublisherSpringer, Springer Nature
Pages295-309
Number of pages15
ISBN (Print)9781493939954
DOIs
Publication statusPublished - 2016

Publication series

NameSpringer Series in Computational Neuroscience
PublisherSpringer

Keywords

  • computed tomography
  • detrended fluctuation analysis
  • fractal dimension
  • Hurst exponent
  • magnetic resonance imaging
  • neuroimaging
  • classification
  • statistical tests

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  • Cite this

    Lahmiri, S., Boukadoum, M., & Di Ieva, A. (2016). Fractals in neuroimaging. In A. Di Ieva (Ed.), The Fractal geometry of the brain (pp. 295-309). (Springer Series in Computational Neuroscience). New York: Springer, Springer Nature. https://doi.org/10.1007/978-1-4939-3995-4_19