scikit-surgerysurfacematch 0.4.5

Description:

scikitsurgerysurfacematch 0.4.5

Author: Matt Clarkson
scikit-surgerysurfacematch is part of the SNAPPY software project, developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL).
scikit-surgerysurfacematch supports Python 3.6 - 3.8
scikit-surgerysurfacematch contains algorithms that are useful in stereo reconstruction from video images, and matching to a pre-operative 3D model, represented as a point cloud.

Features

Base classes (pure virtual interfaces), for video segmentation, stereo reconstruction, rigid registration / pose estimation. See `sksurgerysurfacematch/algorithms`
A base class to handle rectification properly, and the right coordinate transformation, to save you the trouble.
Stereo reconstruction classes based on Stoyanov MICCAI 2010, and OpenCV SGBM reconstruction, using above interface, and both allowing for optional masking.
Rigid registration using PCL’s ICP implementation, which is wrapped in scikit-surgerypclcpp
A pipeline to combine the above, segment a video pair, do reconstruction, and register to a 3D model, where each part can then be swapped with whatever implementation you want, as long as you implement the right interface.
A pipeline to take multiple stereo video snapshots, do surface reconstruction, mosaic them together, and then register to a 3D model. Again, each main component (video segmentation, surface reconstruction, rigid registration) is swappable. Inspired by: [Xiaohui Zhang’s](https://doi.org/10.1007/s11548-019-01974-6) method.



Developing

Cloning
You can clone the repository using the following command:
git clone https://github.com/UCL/scikit-surgerysurfacematch


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 sksurgerysurfacematch



Installing
You can pip install directly from the repository as follows:
pip install git+https://github.com/UCL/scikit-surgerysurfacematch

Contributing
Please see the contributing guidelines.


Useful links

Source code repository
Documentation




Licensing and copyright
Copyright 2020 University College London.
scikit-surgerysurfacematch is released under the BSD-3 license. Please see the license file for details.


Acknowledgements
Supported by Wellcome and EPSRC.