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Protocol for neuron tracing and analysis of dendritic structures from noisy microscopy images using Neuronalyzer
Yael Iosilevskii1, Omer Yuval2, Tom Shemesh1
1Department of Biology, Technion - Israel Institute of Technology, Haifa 32000, Israel.
STAR Protocols
|May 12, 2024
Summary
This study introduces Neuronalyzer software for automatically reconstructing neuronal morphology from microscopy images. The tool enables efficient denoising, segmentation, tracing, and analysis of branched neural structures, even with noisy data.
Area of Science:
- Neuroscience
- Bioimaging
- Computational Biology
Background:
- Accurate analysis of neuronal morphology is crucial for understanding brain function.
- Microscopy data often presents challenges such as noise and complex branched structures.
- Existing methods may lack automation or robustness in handling diverse imaging conditions.
Purpose of the Study:
- To present a protocol for automatic reconstruction of branched neuronal structures from microscopy images.
- To introduce Neuronalyzer software as a tool for this purpose.
- To detail the steps involved in image processing, feature extraction, and data analysis.
Main Methods:
- Utilized Neuronalyzer software for image processing.
- Implemented steps for loading, denoising, segmentation, and tracing of neuron images.
- Performed feature extraction, including branch curvature and junction angles, followed by data analysis and plotting.
Main Results:
- Developed a protocol for automatic reconstruction of neuronal morphology.
- Demonstrated Neuronalyzer's capability for batch processing and statistical comparisons.
- Showcased the software's effectiveness in handling noise and variations in microscopy images.
Conclusions:
- Neuronalyzer provides an automated and robust solution for neuronal morphology analysis.
- The protocol facilitates efficient extraction and analysis of quantitative data from complex neural structures.
- This approach aids in advancing the study of neuronal morphology in neuroscience research.
