Table of Contents

• 1. Introduction
• 2. Installation
• 3. Generating the documentation locally
• 4. IBSI Standardization
  • IBSI Chapter 1
  • IBSI Chapter 2 (In progress)
• 5. Acknowledgement
• 6. Authors
• 7. Statement

1. Introduction

This is an open-source python package for processing and extracting features from medical images. It facilitates the medical-images processing and computation of all types of radiomic features as well as the reproducibility of the different analysis. This package has been standardized with the IBSI norms.

2. Installation

Python installation

The MEDimage package requires python 3.8 or more to be run. If you don't have it installed on your machine, follow the instructions here.

Package installation

You can easily install the MEDimagepackage from PyPI using:

pip install MEDimage

For more installation options (conda, poetry...) check out the installation documentation.

3. Generating the documentation locally

We used sphinx to create the documentation for this project and you check it out in this link. But you can generate and host it locally by compiling the documentation source code using:

cd docs
make clean
make html

Then open it locally using:

cd _build/html
python -m http.server

4. Tutorials

We have created many tutorials for the different functionalities of the package. More details can be found in the documentation

4. IBSI Standardization

The image biomarker standardization initiative (IBSI) is an independent international collaboration which works towards standardizing the extraction of image biomarkers from acquired imaging. The IBSI therefore seeks to provide image biomarker nomenclature and definitions, benchmark data sets, and benchmark values to verify image processing and image biomarker calculations, as well as reporting guidelines, for high-throughput image analysis. We have participated in this collaboration with our package to make sure it respects the international nomenclatures and definitions The participation was separated to two chapters:

• IBSI Chapter 1

  The IBSI chapter 1 was initiated in September 2016, and it reached completion in March 2020 and is dedicated to the standardization of commonly used radiomic features. We have created jupyter notebooks and made it available for the users to run the IBSI tests themselves. The tests are an interactive Colab notebooks and is directly accessible here:

  • Phase 1:
  • Phase 2:

• IBSI Chapter 2 (In progress)

  The IBSI chapter 2 was launched in June 2020 and still in progress. It is dedicated to the standardization of commonly used imaging filters in radiomic studies. We have created jupyter notebooks and made it available for the users to run the IBSI tests themselves and validate image filtering and image biomarker calculations from filter response maps. The tests are an interactive Colab notebooks and is directly accessible here:

  • Phase 1:
  • Phase 2:

  Our team UdeS (a.k.a. Université de Sherbrooke) has already submitted the benchmarked values to the IBSI uploading website and it can be found here: IBSI upload page.

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Miscellaneous

You can avoid the next steps (jupyter installation and environment set up) if you installed the package using conda or poetry according to the documentation.

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You can view & run the tests locally by installing the Jupyter Notebook application on your machine:

python -m pip install jupyter

Then add the installed medimage environment to the jupyter notebook kernels using:

python -m ipykernel install --user --name=medimage

Then access the IBSI tests folder using:

cd notebooks/ibsi/

Finally, launch jupyter notebook to navigate through the IBSI notebooks using:

jupyter notebook

5. Acknowledgement

MEDimage is an open source package that welcome any contribution and feedback. We wish that this package could serve the growing radiomics research community by providing a flexible as well as ibsi standardized tool to reimplement existing methods and develop their own new methods.

6. Authors

• MEDomics: MEDomics consortium.

7. Statement

This package is part of https://github.com/medomics, a package providing research utility tools for developing precision medicine applications.

MIT License

Copyright (C) 2022 MEDomics consortium

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.