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Neuroinformatics

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01-09-2009

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

Authors: Holger Heumann, Gabriel Wittum

Published in: Neuroinformatics | Issue 3/2009

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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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Title: The Tree-Edit-Distance, a Measure for Quantifying Neuronal Morphology
Authors: Holger Heumann
Gabriel Wittum
Publication date: 01-09-2009
Publisher: Humana Press Inc
Published in: Neuroinformatics / Issue 3/2009
Print ISSN: 1539-2791
Electronic ISSN: 1559-0089
DOI: https://doi.org/10.1007/s12021-009-9051-4

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