Medial axis

Filament Tracing LocThresh (ImageJ)


Blood vessels tracing in 3D image from 3D Gaussian blurring (user defined radius), local thresholding (user defined radius and offset) and 3D skeletonization. Dockerized version for BIAFLOWS,

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Filament Tracing Tubeness (ImageJ)


Blood vessels tracing in 3D image from Tubeness filtering (user defined scale), 3D opening (radius set to 2), thresholding (user defined level) and 3D skeletonization.

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Filament Tracing (ImageJ)

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has function
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"The plugin analyzes fluorescence microscopy images of neurites and nuclei of dissociated cultured neurons. Given user-defined thresholds, the plugin counts neuronal nuclei, and traces and measures neurite length."[...]" NeuriteTracer is a fast simple-to-use ImageJ plugin for the analysis of outgrowth in two-dimensional fluorescence microscopy images of neuronal cultures. The plugin performed well on images from three different types of neurons with distinct morphologies."

This plugin requires parameter setting: Threshold levels and scale (see more details on the related publication)



nctuTW is a "high-throughput computer method of reconstructing the neuronal structure of the fruit fly brain. The design philosophy of the proposed method differs from those of previous methods. We propose first to compute the 2D skeletons of a neuron in each slice of the image stack. The 3D neuronal structure is then constructed from the 2D skeletons. Biologists tend to use confocal microscopes for optimal images in a slice for human visualization; and images in two consecutive slices contain overlapped information. Consequently, a spherical object becomes oval in the image stack; that is, neurons in the image stack do not reflect the true shape of the neuron. This is the main reason we chose not to work directly on the 3D volume.

The proposed method comprises two steps. The first is the image processing step, which involves computing a set of voxels that is a superset of the 3D centerlines of the neuron. The shortest path graph algorithm then computes the centerlines. The proposed method was applied to process more than 16 000 neurons. By using a large amount of reconstructions, this study also demonstrated a result derived from the reconstructed data using the clustering technique." (Extracted from reference publication:

Illustrative image shows gold standard (top) and method results (bottom). 


Microtubule Length Analysis



Quantify the length of microtubules (MT) and the MT average density per cell.

Workflow descriptions

Simple two step workflow, allowing visual & manual correction of microtubule between the 2 steps. Batch measurement of microtubule lengths for multiple images is achieved by segmenting the MTs and then their skeletonizations. The number of pixels in the microtubule is proportional to their length, so the length can be estimated.


Workflow is written as an ImageJ macro (Fiji) with following steps:

  1. The enhancement of tubular structure by computing eigenvalues of the hessian matrix on a Gaussian filtered version of the image ( sigma 1 pixel), as implemented in the tubeness plugin.
  2. The tubules were then thresholded , and structures containing less than 3 pixels were discarded.
  3. If needed, a visual check and correction of segmented microtubule is then performed.
  4. After correction, segmented MTs were then reduced to a 1-pixel thick line using the skeletonize plugin of Fiji. The length of the skeletonized microtubules was then directly proportional to their length.
  5. Data were grouped by condition and converted back to micrometers units under Matlab for the statistical tests.


Commented but not that general without editing some fields in the macros.

Sample Data

Sample data and workflow (see above URL) can be accessed by

  • login: biii
  • password Biii!Tag1


3D version also available here.

Use of components Skeletonize and Tubeness Filter

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Neuron studio is a software package to reconstruct neurons from 3D confocal images. Reconstruction can be done manually, semi-manually or fully automatic. The images as well as the detected objects are rendered in 3D. A spine detection and classification function is also included. Results can be exported as a text file with coords of the spines. It seems that active development has stopped in 2009. NeuronStudio is being developed at the Computational Neurobiology and Imaging Center (CNIC), a research laboratory at the Neuroscience Department of the Mount Sinai School of Medicine in New York.

NeuronStudio can be used with default parameters or user-defined parameters (Fully or semi-automated).


Strahler Analysis


This plugin performs Strahler analysis on topographic skeletons (2D/3D). Strahler numbering is a numerical procedure that summarizes the branching complexity of mathematical trees.

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