AutoNeuron Features

AutoNeuron is designed to automatically trace image stacks without image preprocessing. The simplified user interface allows for adjustment of basic tracing parameters, followed by a visual display of the model superimposed over the image stack projection.

Tracing Features

Trace confocal images in 3D
Trace confocal images in 3D

  • Trace typical stacks in less than 60 seconds
  • Trace from 3D image stacks and 3D images
  • Use confocal fluorescent and brightfield
  • Exclude branches detached from soma
  • Soma halo suppression
  • Trace through process gaps
  • Faint image detection setting
  • Deconvolution is not necessary
  • Noise tolerant algorithm

Editing Features

Trace brightfield and fluorescent images and stacks
Trace 2D images from cell cultures

  • Add and remove traced points
  • Detach and reconnect branches and trees
  • Shift tree location
  • Adjust branch diameter
  • Insert or remove branch nodes
  • Extend existing branches
  • Splice disconnected branch segments

Reconstruction Model Output

  • Fully-editable output model
  • Compatible with Neurolucida format


Process diameter of branching
structures is automatically recorded

  • Generates 3D vector-based model
  • Branches represented as tapered cylinders (conical frusta)
  • Somas represented as contour sets
  • Full branch length, order, volume, surface area analysis with Neurolucida Explorer
  • Volume and shape analysis of soma models with Neurolucida Explorer

Graphics Output Features

  • Rotate model through XYZ axes
  • Correct for histological shrinkage
  • Display with/without process thickness
  • Export branch analysis to spreadsheet format

Neurolucida Explorer - Screen Shot
Neurolucida Explorer provides the
ability to view tracing models and
perform detailed morphometric analysis
of branching structures

Morphometric Analysis

Neurolucida Explorer automatically performs morphometric analysis of data collected with AutoNeuron. The tracings acquired in AutoNeuron consist of trees describing the branching pattern of neurons, and markers indicating the location of cells or other small structures. Acquiring this data in three dimensions allows for quantitative analysis of how cells are organized. The morphometric analysis performed by Neurolucida Explorer measures lengths, areas, population sizes, tree branching patterns, and many other quantifiable parameters. Neurolucida Explorer provides the tools for analyzing this data in both single and serial sections, allowing for full volumetric analysis of solid objects, and reconstructions of neuronal trees that show tree thickness and volume, branching characteristics, spine density, etc.