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FLIMatch

FLIMatch is a Python toolkit for matching, comparing, and classifying fluorescence lifetime imaging microscopy (FLIM) data across experiments, conditions, or samples.

The package focuses on lifetime-domain similarity rather than raw intensity, enabling robust comparison of FLIM measurements acquired under varying photon counts, signal levels, or imaging conditions.

FLIMatch is designed for reproducible, quantitative analysis workflows in biophysics and fluorescence microscopy.


Features

  • Lifetime-based matching and similarity metrics
  • Comparison of FLIM distributions across samples or conditions
  • Tools for clustering and classification in lifetime space
  • Support for pixel-wise and region-based analysis
  • Designed to integrate with FLIM, FRET, and TCSPC pipelines

Installation

Clone the repository and install dependencies:

git clone https://github.com/C-Trass/FLIMatch.git
cd FLIMatch
pip install -r requirements.txt

Who is this for?

FLIMatch is intended for:

  • FLIM users comparing lifetime data across experiments or conditions
  • Researchers interested in lifetime-based classification or matching
  • Users working with heterogeneous or low-photon FLIM datasets
  • Scientists who want quantitative alternatives to intensity-based comparisons

Citation

If you use FLIMatch in academic work, please cite:

Dr Conor A. Treacy, FLIMatch: Lifetime-based matching and comparison of fluorescence lifetime imaging data, Biomedical Optics Express, forthcoming.

A DOI will be added here once the associated methods paper is published.

Until then, you may cite this repository directly using the GitHub URL and the software version.


License

This project is released under the MIT License. You are free to use, modify, and distribute the code with attribution.


Contact

Maintained by Conor Treacy 📫 Contact: LinkedIn | Email

From photons to plots.

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FLIMatch is a Python toolkit for matching, comparing, and classifying fluorescence lifetime imaging microscopy (FLIM) data across experiments, conditions, or samples.

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