Neurons and fractals: how reliable and useful are calculations of fractal dimensions?
In the past 15 years it has become possible to determine the fractal dimension (Df) of complex objects, including neurons, by automated image analysis methods. However, there are many unresolved issues that need to be addressed. In this paper we discuss how the Df calculated by different methods may vary and how fractal analysis may be of use for retinal ganglion cell characterization. The goal of this work was to acknowledge inherent sources of variation during measurement and evaluate current fractal analysis methods for describing structure. Our results show that different algorithms and even the same algorithm performed by different computer programs and/or experimenters may give different but consistent numerical values. All described methods demonstrated their suitability for classifying cat retinal ganglion cells into distinct groups. Our results reinforce the idea that comparison of measurements of different profiles using the same measurement method may be useful and valid even if an exact numeric value of the dimension is not realised in practice.
School of Community Health, Charles Sturt University, Albury, NSW, Australia.
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Jelinek
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Fernandez
D000818:Animals; D017709:Fractals; D008962:Models, Theoretical; D009474:Neurons / Q000166:cytology / Q000502:physiology*