scikit-surgeryimage implements image processing tools and alogrithms for Image Guided Surgery.
scikit-surgeryimage is a python only project to implement image processing algorithms that are useful for image-guided surgery.
scikit-surgeryimage was developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences in University College London (UCL).
requirements.txt specifies a dependency on opencv-contrib-python-headless, so you can use any OpenCV python therein. In addition, this project provides:
- Convenience classes for video read and write.
- Utilities to detect the number of cameras and prepare text for overlay on video.
- A PointDetector interface for video camera calibration and implementations such as OpenCV chessboard, ArUco, ChArUco and combinations.
- Generate ChArUco patterns
- Interlacing and deinterlacing.
- Convenience wrappers for erosion and dilation.
You can pip install directly from the repository as follows:
pip install scikit-surgeryimage
You can clone the repository using the following command:
git clone https://github.com/SciKit-Surgery/scikit-surgeryimage
Running the tests
You can run the unit tests by installing and running tox:
pip install tox tox
Please check list of common issues.
Please see the contributing guidelines.
Licensing and copyright
Copyright 2018 University College London. scikit-surgeryimage is released under the BSD-3 license. Please see the license file for details.
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