Blood Perfusion Visualization (NDVI-style)

Tissue oxygenation has a spectral signature: oxy- and deoxy-haemoglobin absorb light differently across the visible and near-infrared range. This tutorial builds a normalised-difference (NDVI-style) pipeline that maps that contrast into an intuitive false-colour visualisation of blood perfusion.

The pipeline runs on the XMR_Demo_Blood_Perfusion dataset and renders side-by-side frames showing tissue, perfusion overlay, and false-RGB.

Run the example:

• examples/blood_perfusion/nd_blood_perfusion.py — cuvis-ai-cookbook
• Dataset on HuggingFace — also surfaced in the datasets catalog

What you'll learn

• Building a normalised-difference index across two hyperspectral bands.
• Producing false-RGB output suitable for clinical or demo settings.
• Saving the rendered frames as a video artifact.

When to reach for this pattern

• Any biological signal with a known two-band differential (NDVI for vegetation, NDWI for water, blood perfusion for tissue).
• You want a visualisation pipeline that runs in real time from a streaming camera.
• You want a baseline before reaching for learned tissue classifiers.