scikit-surgeryfredbackend

FRED provides an interactive demonstration of fiducial based registration for teaching purposes


Keywords
medical, imaging
License
DSDP
Install
pip install scikit-surgeryfredbackend==0.0.6

Documentation

Fiducial Registration Educational Demonstration

Logo GitHub Actions CI status Test coverage Documentation Status The SciKit-Surgery paper DOI - Zenodo Video Demonstration on YouTube Video Demonstration of Game on YouTube

Author: Stephen Thompson

Fiducial Registration Educational Demonstration (SciKit-SurgeryFRED) is part of the SciKit-Surgery software project, developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL). This repository only contains the backend functions, not any user interface.

Fiducial Registration Educational Demonstration is tested with Python 3.X

Fiducial Registration Educational Demonstration is intended to be used as part of an online tutorial in using fiducial based registration. The tutorial covers the basic theory of fiducial based registration, which is used widely in image guided interventions. The tutorial aims to help the students develop an intuitive understanding of key concepts in fiducial based registration, including Fiducial Localisation Error, Fiducial Registration Error, and Target Registration Error.

Please explore the project structure, and implement your own functionality.

Citing

If you use SciKit-SurgeryFRED in your research or teaching please cite it. Individual releases can be cited via the Zenodo tag. SciKit-Surgery should be cited as:

Thompson S, Dowrick T, Ahmad M, et al. "SciKit-Surgery: compact libraries for surgical navigation." International Journal of Computer Assisted Radiology and Surgery. 2020 May. DOI: 10.1007/s11548-020-02180-5.

Developing

Cloning

You can clone the repository using the following command:

git clone https://github.com/UCL/scikit-surgeryfredbackend

Running tests

Pytest is used for running unit tests:

pip install pytest
python -m pytest

Linting

This code conforms to the PEP8 standard. Pylint can be used to analyse the code:

pip install pylint
pylint --rcfile=tests/pylintrc sksurgeryfredbackend

Installing

You can pip install directly from the repository as follows:

pip install git+https://github.com/UCL/scikit-surgeryfredbackend

Contributing

Please see the contributing guidelines.

Useful links

Licensing and copyright

Copyright 2020 University College London. Fiducial Registration Educational Demonstration is released under the BSD-3 license. Please see the license file for details.

Acknowledgements

Supported by Wellcome and EPSRC.