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Python Examples

All the python examples can be found in the repository. You can also find many examples in the python tutorials.

ExampleResult
Load an image and display itImage;" />
Load an whole slide image (WSI) and display itImage;" />
Convert a numpy ndarray image to a FAST image and display it
Generate tissue patches from a whole slide image WSIImage;" />
Filter an image in FAST, convert it to numpy ndarrays and display it with matplotlibImage;" />
Neural network segmentation of ultrasound imagesImage;" />
Export visualization of ultrasound video segmentation to a video fileImage;" />
Capture individual frames of a video file, convert to images and display with matplotlibImage;" />
Display orthogonal slices of 3D CT data with segmentation overlayImage;" />
Display orthogonal slices of 3D MRI data with segmentation overlayImage;" />
Block matching based ultrasound speckle trackingImage;" />
Stream images from webcamera and apply edge detectionImage;" />
Stream images from Clarius ultrasound scanner and apply a non-local means (NLM) filterImage;" />
Extract surface mesh from CT volume and render using GPU-based Marching Cubes algorithmImage;" />
Create a rotating GIF of a 3D volumeImage;" />
Inject Python code into a FAST pipeline by creating a custom Python process objectImage;" />
GPU image processing with OpenCL in PythonImage;" />
Create a custom data streamer in PythonImage;" />
Create a custom random access streamer with playback GUI in PythonImage;" />
Creating a Qt GUI with PySide2 along FASTImage;" />
Using FAST in an existing PySide2 applicationImage;" />
Real-time line plottingImage;" />
Controlling a FAST surface extraction pipeline with a Qt GUI using PySide2Image;" />
Stream ultrasound file format (UFF) data, apply non-local means and displayImage;" />
Stream ultrasound file format (UFF) data and display with matplotlibImage;" />
Perform envelope detection, log compression and scan conversion on ultrasound IQ dataImage;" />
Beamform ultrasound file format (UFF) data with VBeam and process & visualize with FASTImage;" />