NeuronMetrics: Software for Semi-Automated Processing of Cultured-Neuron Images

Case ID:

Thanks for your interest in NeuronMetrics. To download this software please click on the License This Technology link at right, and choose the appropriate use for commercial or academic purposes. The user manual can be downloaded at the bottom link in the right hand column. Once you have completed the license agreement you will be sent a download link and the additional files to make the software operational.


This invention comprises a software tool, NeuronMetrics, which functions as a set of modules that run in the open-source program ImageJ. NeuronMetrics features a novel method for estimating neural “branch number” (a measure of the axonal complexity) from two-dimensional images. In addition, the tool features a novel method for modeling neural structure in large “gaps” that result from image artifacts. NeuronMetrics and a detailed user guide will be available for download at iBridge. The program is user-friendly and easy to learn, making it a useful screening tool for basic and applied research.



Many mutations and drug compounds affect neural function by altering the shape and density of neuron networks, changes that can easily be seen by analyzing still images of prepared neuron cultures that have been genetically altered or exposed to experimental compounds. Drug discovery for developmental brain disorders lags decades behind that in other conditions, however, largely because existing cell-based screening assays are laborious to analyze accurately. A new software application, NeuronMetrics, can greatly improve the speed and accuracy of neuron-culture image analysis, potentially making it possible to process hundreds of such images each day.



  • Can process roughly 60 two-dimensional images in 60 to 180 minutes
  • Complementary to other neuron-image processing software tools
  • Can analyze certain in vivo images
  • Calculated neural “branch counts” from neurite-contact information, improving analysis accuracy
  • Automatically “fills” large gaps in the neural network, expanding the accuracy of neural models



  • In vitro screening of potential drug compounds for neural efficacy or toxicity
  • In vitro studies of genetic or drug effects on neural-net structure
Patent Information:
Contact For More Information:
Rakhi Gibbons
Director of Licensing & IP
The University of Arizona
Lead Inventor(s):
Linda Restifo
Alon Efrat
Martha Narro
Robert Kraft
Fan Yang
Carola Wenk