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NeuroscienceNature Methods
Peer-reviewed journal article

SNT: A Unifying Toolbox for Quantification of Neuronal Anatomy

Cameron ArshadiiD, Ulrik GüntheriD, Mark EddisoniD, Kyle HarringtoniD, Tiago FerreiraiD

Abstract

Quantification of neuronal morphology is essential for understanding neuronal connectivity and many software tools have been developed for neuronal reconstruction and morphometry. However, such tools remain domain-specific, tethered to specific imaging modalities, and were not designed to accommodate the rich metadata generated by recent whole-brain cellular connectomics. To address these limitations, we created SNT: a unifying framework for neuronal morphometry and analysis of single-cell connectomics for the widely used Fiji and ImageJ platforms. We demonstrate that SNT can be used to tackle important problems in contemporary neuroscience, validate its utility, and illustrate how it establishes an end-to-end platform for tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy. With an open and scriptable architecture, a large user base, and thorough community-based documentation, SNT is an accessible and scalable resource for the broad neuroscience community that synergizes well with existing software.

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02 /Specification & Classification

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