NeuronCyto II: An automatic and quantitative solution for crossover neural cells in high throughput screening

Area of Science:

• Neuroscience
• Biotechnology
• Computational Biology

Background:

• Microscopy generates large image datasets (e.g., High Throughput Screening, 4D imaging) requiring automated analysis.
• Quantifying neuronal morphology (neurite number, length, branching) is crucial in neurobiology.
• The neurite "crossover" problem complicates accurate automated morphological analysis.

Purpose of the Study:

• To present NeuronCyto II, a software solution for the "crossover" problem in neuronal morphology quantification.
• To provide an interactive and user-friendly tool for automatic neurite analysis.
• To improve the reliability and accuracy of neuronal morphology quantification, especially in cases of neurite crossing.

Main Methods:

• Development of NeuronCyto II software with a graphical user interface (GUI).
• Implementation of a solution for the "crossover" problem based on directed graph theory.
• Integration of methods for processing neurites with and without crossovers.

Main Results:

• NeuronCyto II effectively quantifies neuronal morphology automatically.
• The software significantly improves the reliability and accuracy of analyzing neurons with "crossover" issues.
• The Result Inspector allows users to interact with image data and numerical features.

Conclusions:

• NeuronCyto II provides a robust solution to the challenging "crossover" problem in neuronal morphology.
• The software is user-friendly, enabling routine quantitative analysis of complex neuronal images.
• NeuronCyto II is freely available, promoting wider use in neurobiology research.