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| Main Authors: | , , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15355995 |
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Table of Contents:
- <p>The analysis of optical microscopy images to extract statistical information on tumoral cell morphology is crucial to a lot of biological research projects. However, currently available tools often lack the capability to iteratively analyse large datasets of images contained in a .lif file with high accuracy, while maintaining relatively low processing times per image. To remove this bottleneck, we developed a Python script that overcomes these limitations, enabling faster and more precise analysis of large image datasets containing hundred of cells per image. This new tool has proven to be highly accurate in counting the number of cells, while maintaining a low processing time per image.</p>