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The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology

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Abstract

The shape of neuronal cells strongly resembles botanical trees or roots of plants. To analyze and compare these complex three-dimensional structures it is important to develop suitable methods. We review the so called tree-edit-distance known from theoretical computer science and use this distance to define dissimilarity measures for neuronal cells. This measure intrinsically respects the tree-shape. It compares only those parts of two dendritic trees that have similar position in the whole tree. Therefore it can be interpreted as a generalization of methods using vector valued measures. Moreover, we show that our new measure, together with cluster analysis, is a suitable method for analyzing three-dimensional shape of hippocampal and cortical cells.

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  1. http://neura.org

  2. http://neuromorpho.org

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Correspondence to Gabriel Wittum.

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This research has been funded by BMBF.

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Heumann, H., Wittum, G. The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology. Neuroinform 7, 179–190 (2009). https://doi.org/10.1007/s12021-009-9051-4

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  • DOI: https://doi.org/10.1007/s12021-009-9051-4

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