https://github.com/biomedical-imaging-group/psf_generator

PSF Generator: a PyTorch-based library to simulate point spread functions for microscopes.
https://github.com/biomedical-imaging-group/psf_generator

fluorescence-microscopy psf

Last synced: 11 months ago
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PSF Generator: a PyTorch-based library to simulate point spread functions for microscopes.

• Host: GitHub
• URL: https://github.com/biomedical-imaging-group/psf_generator
• Owner: Biomedical-Imaging-Group
• License: mit
• Created: 2024-01-23T18:44:58.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-07-08T17:30:01.000Z (12 months ago)
• Last Synced: 2025-07-08T18:51:01.838Z (12 months ago)
• Topics: fluorescence-microscopy, psf
• Language: Python
• Homepage:
• Size: 35.1 MB
• Stars: 10
• Watchers: 4
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# PSF-Generator

[![MIT License](https://img.shields.io/github/license/Biomedical-Imaging-Group/psf_generator)](https://github.com/Biomedical-Imaging-Group/psf_generator/raw/main/LICENSE)

[![PyPI](https://img.shields.io/pypi/v/psf-generator.svg?color=green)](https://pypi.org/project/psf-generator)

[![Python Version](https://img.shields.io/pypi/pyversions/psf-generator.svg?color=green)](https://python.org)

***

Welcome to the psf-generator library!

This library contains a high-performance PyTorch implementation of precise physical models to compute the point spread function (PSF) of optical microscopes. 

The PSF characterizes the response of an imaging system to a point source and is crucial for tasks such as deconvolution, correction of aberrations, and characterization of the system.

We classify these models in two types—scalar or vectorial—and in both cases the PSF integral can be computed in Cartesian or spherical coordinate systems. 

This results in the following four _propagators_

| Name of propagator             |         Other names         |

|--------------------------------|:---------------------------:|

| `ScalarCartesianPropagator`    | simple/scalar Fourier model |

| `ScalarSphericalPropagator`    |       Kirchhoff model       |

| `VectorialCartesianPropagator` |   vectorial Fourier model   |

| `VectorialSphericalPropagator` |     Richards-Wolf model     |

For details on the theory, please refer to 

[Revisiting PSF models: unifying framework and high-performance implementation](https://arxiv.org/html/2502.03170v1).

# Documentation

Documentation can be found here: https://psf-generator.readthedocs.io/

# Installation

## Basic Installation

```

pip install psf-generator

```

That's it for the basic installation; you're ready to go!

## Developer Installation

If you're interested in experimenting with the code base, please clone the repository and install it using the following commands:

```

git clone git@github.com:Biomedical-Imaging-Group/psf_generator.git

cd psf_generator

pip install -e .

```

# Demos

Jupyter Notebook demos and Python scripts can be found under `demos/`.

# Napari Plugin

You can find our Napari plugin [here](https://github.com/Biomedical-Imaging-Group/napari-psfgenerator).

# Cite Us

```Liu, Yan, Vasiliki Stergiopoulou, Jonathan Chuah, Michael Unser, Daniel Sage, and Jonathan Dong. Revisiting PSF models: unifying framework and high-performance implementation. arXiv preprint [arXiv:2502.03170](https://arxiv.org/abs/2502.03170), 2025.```