Metadata-Version: 2.1
Name: scikit-surgeryfredbackend
Version: 0.0.6
Summary: FRED provides an interactive demonstration of fiducial based registration for teaching purposes
Home-page: https://github.com/UCL/scikit-surgeryfredbackend
Author: Stephen Thompson
Author-email: s.thompson@ucl.ac.uk
License: BSD-3 license
Description: Fiducial Registration Educational Demonstration
        ===============================================
        
        .. image:: https://github.com/UCL/scikit-surgeryfredbackend/raw/master/project-icon.png
           :height: 128px
           :width: 128px
           :target: https://github.com/UCL/scikit-surgeryfredbackend
           :alt: Logo
        
        .. image:: https://github.com/UCL/scikit-surgeryfredbackend/workflows/.github/workflows/ci.yml/badge.svg
           :target: https://github.com/UCL/scikit-surgeryfredbackend/actions
           :alt: GitHub Actions CI status
        
        .. image:: https://coveralls.io/repos/github/UCL/scikit-surgeryfredbackend/badge.svg?branch=master&service=github
            :target: https://coveralls.io/github/UCL/scikit-surgeryfredbackend?branch=master
            :alt: Test coverage
        
        .. image:: https://readthedocs.org/projects/scikit-surgeryfredbackend/badge/?version=latest
            :target: http://scikit-surgeryfredbackend.readthedocs.io/en/latest/?badge=latest
            :alt: Documentation Status
        
        .. image:: https://img.shields.io/badge/Cite-SciKit--Surgery-informational
           :target: https://doi.org/10.1007/s11548-020-02180-5
           :alt: The SciKit-Surgery paper
        
        .. image:: https://zenodo.org/badge/269602581.svg
           :target: https://zenodo.org/badge/latestdoi/269602581
           :alt: DOI - Zenodo
        
        .. image:: https://img.shields.io/badge/Video-Registration-blueviolet
           :target: https://www.youtube.com/watch?v=t_6CH5uroYo
           :alt: Video Demonstration on YouTube
        
        .. image:: https://img.shields.io/badge/Video-Game-blueviolet
           :target: https://www.youtube.com/watch?v=ansH1w2ST-g
           :alt: 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
        ^^^^^^^^^^^^
        
        * `Source code repository`_
        * `Documentation`_
        
        
        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`_.
        
        
        .. _`Wellcome EPSRC Centre for Interventional and Surgical Sciences`: http://www.ucl.ac.uk/weiss
        .. _`source code repository`: https://github.com/UCL/scikit-surgeryfred
        .. _`Documentation`: https://scikit-surgeryfredbackend.readthedocs.io
        .. _`SciKit-Surgery`: https://scikit-surgery.org
        .. _`University College London (UCL)`: http://www.ucl.ac.uk/
        .. _`Wellcome`: https://wellcome.ac.uk/
        .. _`EPSRC`: https://www.epsrc.ac.uk/
        .. _`contributing guidelines`: https://github.com/UCL/scikit-surgeryfredbackend/blob/master/CONTRIBUTING.rst
        .. _`license file`: https://github.com/UCL/scikit-surgeryfredbackend/blob/master/LICENSE
        
        
Keywords: medical imaging
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Description-Content-Type: text/x-rst
