SciKit-Surgery libraries implements a family of compact, orthogonal, libraries accompanied by robust testing, documentation, and quality control. SciKit-Surgery libraries can be rapidly assembled into testable clinical applications and subsequently translated to production software without the need for software reimplementation.
Wondering which library is suitable for your job and how to use it? Check out the list of included libraries, relevant documentation and demo tutorials.
| Library | Purpose |
|---|---|
| scikit-surgerycore | Algorithms/tools common to all scikit-surgery packages |
| scikit-surgeryimage | Image processing algorithms using OpenCV |
| scikit-surgeryvtk | Implements VTK functionality for IGS applications |
| scikit-surgeryutils | Example applications/utilities |
| scikit-surgerycalibration | Calibration algorithms (camera/pointer/ultrasound etc) |
| scikit-surgerysurfacematch | Stereo reconstruction and point cloud matching |
| scikit-surgerytf | IGS models implemented in TensorFlow |
| scikit-surgerytorch | IGS models implemented in PyTorch |
| scikit-surgerynditracker | Interface for Northern Digital (NDI) trackers. Vicra, Spectra, Vega, Aurora. |
| scikit-surgeryarucotracker | Interface for OpenCV ARuCo. |
| scikit-surgeryspeech | Speech/Wakeword detection |