brighteyes-ism 1.2.1

A toolbox for analysing and simulating ISM images

BrightEyes-ISM

A toolbox for analysing and simulating Image Scanning Microscopy (ISM) datasets. The analysis module contains libraries for:

• Adaptive Pixel Reassignment (https://doi.org/10.1038/s41592-018-0291-9)
• Focus-ISM (https://doi.org/10.1038/s41467-022-35333-y)
• Image Deconvolution (https://doi.org/10.1088/1361-6420/accdc5)
• Fourier Ring Correlation (https://doi.org/10.1038/s41467-019-11024-z)

The simulation module contains libraries for:

• Generation of ISM point spread functions (https://doi.org/10.1016/j.cpc.2022.108315)
• Generation of tubulin phantom samples

The dataio module contains libraries for:

• Reading the data and metadata from the MCS software (https://github.com/VicidominiLab/BrightEyes-MCS)

---

Installation

You can install brighteyes-ism via pip directly from GitHub:

pip install git+https://github.com/VicidominiLab/BrightEyes-ISM

or using the version on PyPI:

pip install brighteyes-ism

It requires the following Python packages

numpy
scipy
matplotlib
scikit-image
scikit-learn
poppy
PyCustomFocus
h5py
tqdm
statsmodels
matplotlib-scalebar

Documentation

You can find an example of usage here:

https://github.com/VicidominiLab/BrightEyes-ISM/tree/main/examples

You can read the manual of this package on Read the Docs:

https://brighteyes-ism.readthedocs.io

Citation

If you find BrightEyes-ISM useful for your research, please cite it as:

Zunino, A., Slenders, E., Fersini, F. et al. Open-source tools enable accessible and advanced image scanning microscopy data analysis. Nat. Photon. (2023). https://doi.org/10.1038/s41566-023-01216-x

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the GNU GPL v3.0 license, "BrightEyes-ISM" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.