QuPath guide for H-DAB Cell Counting Docs
This is project as been developed by Andrea Nüesch, Univeristy of Sheffield, in collaboration with Maria Paola Ferri, Barcelona Supercomputing Center, Universitat de Barcelona.
Last updated
This is project as been developed by Andrea Nüesch, Univeristy of Sheffield, in collaboration with Maria Paola Ferri, Barcelona Supercomputing Center, Universitat de Barcelona.
Last updated
To follow this step-by-step Guide no previous knowledge of QuPath, Git Bash, or Python is needed. All you need to follow in this tutorial is H-DAB stained, slide-scanned samples. The installation of the programs/software needed and the explanation of how to navigate through them can all be found in this Gitbook.
If you use this step by step guide, please cite the paper below:
Nüesch, A., Ferri, M. P., & Le Maitre, C. L. (2025). Application and Validation of Semiautomatic Quantification of Immunohistochemically Stained Sections for Low Cellular Tissue Such as Intervertebral Disc Using QuPath. JOR Spine, 8(1), e70054. https://doi.org/10.1002/jsp2.70054
QuPath is an open-source software for bioimage analysis and is often used for digital pathology. Its user-friendly interface, built-in algorithms for tissue and cell detection, the ability for interactive machine learning, and the possibility for automated scripting provide a powerful tool for whole slide image analysis.
This project aimed to create a script for semi-automatic cell counting in QuPath, particularly for tissues with high extracellular matrix-to-cell ratio, which produces reproducible immunopositivity rates, with high accuracy, and reduced time to evaluate the samples and is a non-black-box approach.
We advise you to use the processMRXS Package tutorial for the conversion of the text result files from QuPath. If you do not want to use the code to convert the files and merge them, they can be manually opened in Excel and further analysed from there.
License:
Bankhead, P. et al. QuPath: Open source software for digital pathology image analysis. Scientific Reports (2017).
This guide is for the QuPath extension for H-DAB Cell counting and classification in tissue and has been specifically developed within the project.
The docs will consist of two sections:
We've put together some helpful guides, for you to get set up with our product quickly and easily, for expert or non-expert usage.
