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scikit-surgery

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Documentation Status

The SciKit-Surgery paper

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SciKit-Surgery is a collection of compact libraries developed for surgical navigation. Individual libraries can be combined using Python to create clinical applications for translational research. However because each application's requirements are unique the individual SciKit-Surgery libraries are kept independent, enabling them to be maintained, modified and combined in new ways to create new clinical applications. Keeping the libraries independent enables researchers to implement novel algorithms within a small library that can be readily reused and built on by the research community.

A typical clinical application might consist of an imaging source (e.g. SciKit-SurgeryBK to stream ultrasound images), a tracking source (e.g. SciKitSurgery-NDITracker) to locate the images in space, an image processor (e.g. SciKit-SurgeryTorch) to segment anatomy from the image, and a visualisation layer (e.g. SciKit-SurgeryVTK)

SciKit-Surgery is developed at the Wellcome EPSRC Centre for Interventional and Surgical Sciences, part of University College London (UCL).

Packages

Please see Documentation for further module details.

Tutorials

Tutorials are split into three groups, those that show how to assemble SciKit-Surgery libraries into an application, those that concentrate on the workings a single application, and those that are aimed at general education in image guided interventions using SciKit-Surgery.

General Tutorials

* ROS Integration scikit-surgeryvtk

scikit-surgeryimage

scikit-surgerycalibration

* Camera Calibration

Educational Tutorials

Encountering Problems?

Please check list of common issues.

Contributing

Please see the contributing guidelines.

Copyright 2018 University College London. scikit-surgery is released under the BSD-3 license. Please see the license file for details.

Acknowledgements

Supported by Wellcome and EPSRC.