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Updated: Jul 2, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Live neuron morphology automatically reconstructed from multiphoton and confocal imaging data
Bradley E Losavio1, Yong Liang, Alberto Santamaría-Pang
1Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.
Abstract:
We have developed a fully automated procedure for extracting dendritic morphology from multiple three-dimensional image stacks produced by laser scanning microscopy. By eliminating human intervention, we ensure that the results are objective, quickly generated, and accurate. The software suite accounts for typical experimental conditions by reducing background noise, removing pipette artifacts, and aligning multiple overlapping image stacks. The output morphology is appropriate for simulation in compartmental simulation environments. In this report, we validate the utility of this procedure by comparing its performance on live neurons and test specimens with other fully and semiautomated reconstruction tools.

