The constrained tree-edit-distance provides a computationally practical<br />method for comparing morphologies directly without first extracting<br />distributions of other metrics. The application of the constrained<br />tree-edit-distance to hippocampal dendrites by Heumann and Wittum<br />is reviewed and considered in the context of other applications and<br />potential future uses. The method has been used on neuromuscular<br />projection axons for comparisons of topology as well as on trees<br />for comparing plant architectures with particular parameter sets<br />that may inform future efforts in comparing dendritic morphologies.<br />While clearly practical on a small scale, testing and extrapolation<br />of run-times raise questions as to the practicality of the constrained<br />tree-edit-distance for large-scale data mining projects. However,<br />other more efficient algorithms may make use of it as a gold standard<br />for direct morphological comparison.
Gillette, T. A., & Grefenstette, J. J. (2009). On comparing neuronal morphologies with the constrained tree-edit-distance. Neuroinformatics, 7(3), 191–194. https://doi.org/10.1007/s12021-009-9053-2