Box-counting and multifractal analysis in neuronal and glial classification

Herbert Jelinek, Nebojsa T. Milosevic, Audrey Karperien, Bojana Krstonosic

Research output: Book chapter/Published conference paperChapter (peer-reviewed)

6 Citations (Scopus)

Abstract

Fractal analysis in the neurosciences has advanced over the past twenty years. The fractal dimension, besides its ability to discriminate among different cell types, can work as a reliable parameter in cell classification. A qualitative analysis of the morphology of neurons and glia cell types involves a detailed description of the structure and features of cells, and accordingly, their classification into defined classes and types. This paper outlines how fractal analysis can be used for further quantitative classification of these cell types using box-counting and multifractal analysis.
Original languageEnglish
Title of host publicationAdvances in intelligent control systems and computer science
EditorsL. Dumitrache
Place of PublicationBerlin
PublisherSpringer-Verlag London Ltd.
Pages177-189
Number of pages13
ISBN (Print)9783642325472
DOIs
Publication statusPublished - 2013

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer-Verlag London Ltd.
Volume187
ISSN (Electronic)2194-5357

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  • Cite this

    Jelinek, H., Milosevic, N. T., Karperien, A., & Krstonosic, B. (2013). Box-counting and multifractal analysis in neuronal and glial classification. In L. Dumitrache (Ed.), Advances in intelligent control systems and computer science (pp. 177-189). (Advances in Intelligent Systems and Computing; Vol. 187). Springer-Verlag London Ltd.. https://doi.org/10.1007/978-3-642-32548-9_13