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Relaxed multi-levelset segmentation package, with tomographically consistent refinement.

This package provides the following functionalities:

  • Linear relaxation of multi-levelset based segmentation
  • Total Variation (TV) and Laplacian (smoothness) based denoising
  • Estimation of the segmentation gray values
  • Refinement of the segmentation, based on the local reconstructed residual error (RRE)

It contains the code used for the following paper, which also provides a mathematical description of the concepts and algorithms used here:

  • H. Der Sarkissian, N. Viganò, and K. J. Batenburg, “A Data Consistent Variational Segmentation Approach Suitable for Real-time Tomography,” Fundam. Informaticae, vol. 163, pp. 1–20, 2018.

Further information:

Getting Started

It takes a few steps to setup PyRMLSeg on your machine. We recommend installing Anaconda package manager for Python 3.

Installing with conda

Simply install with:

conda install -c cicwi rmlseg

Installing from source

To install PyRMLSeg, simply clone this GitHub project. Go to the cloned directory and run PIP installer:

git clone
cd rmlseg
pip install -e .

Running the examples

To learn more about the functionality of the package check out our examples folder.

Authors and contributors

  • Nicola VIGANÒ - Initial work
  • Henri DER SARKISSIAN - Initial work

See also the list of contributors who participated in this project.

How to contribute

Contributions are always welcome. Please submit pull requests against the master branch.

If you have any issues, questions, or remarks, then please open an issue on GitHub.


This project is licensed under the MIT License - see the file for details.


Relaxed multi-levelset segmentation package, with tomographically consistent refinement.








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