Skip to content
This repository has been archived by the owner on Feb 9, 2022. It is now read-only.


Repository files navigation


PyPI - Python Version PyPI - Format PyPI - Status

PyPi | docs

Radial Image Analysis Toolkit (RadIAnTkit)j is a Python3.8+ package containing tools for full-stack image analysis - from proprietary format conversion to tiff to cellular nuclei segmentation, from the selection of G1 nuclei to the measurement of radial patterns.

Features (in short)

  • Convert proprietary microscope formats CZI (Zeiss) and ND2 (Nikon) to open-source TIFF format.
  • Segment cellular nuclei or other objects, in 2D or 3D, in an unsupervised manner.
    Then use the automatic segmentation to estimate background and foreground intensity.
  • Select cellular nuclei, in G1-phase of the cell cycle, based on DNA staining and nuclear volume.
  • Extract segmented objects and measure their features (e.g., volume, integral of intensity, shape descriptors).
  • Measure radial patterns as radial profiles (with different center definitions),
    and characterize them (e.g., peaks, inflection points, contrast).
  • Generate snakemake-based workflows for seamless integration into fully reproducible streamlined analysis pipelines.

For more available features, check out our docs!


radiantkit has been tested with Python 3.8 and 3.9. We recommend installing it using pipx (see below) to avoid dependency conflicts with other packages. The packages it depends on are listed in our dependency graph. We use poetry to handle our dependencies.


We recommend installing radiantkit using pipx. Check how to install pipx here if you don't have it yet!

Once you have pipx ready on your system, install the latest stable release of radiantkit by running:

pipx install radiantkit

If you see the stars (✨ 🌟 ✨), then the installation went well!

Alternatively, you can use pipx (v0.15.5+) to install directly from git, with the command:

pipx install git+ --force


Run: radiant -h.

All RadIAnTkit tools are accessible from the terminal using the radiant keyword.

usage: radiant [-h] [--version] sub_command ...


We welcome any contributions to radiantkit. In short, we use black to standardize code format. Any code change also needs to pass mypy checks. For more details, please refer to our contribution guidelines if this is your first time contributing! Also, check out our code of conduct.


MIT License - Copyright (c) 2020-21 Gabriele Girelli