Case Study: University of Nottingham achieves faster, highly accurate hyperspectral oxygen-saturation mapping with MathWorks

The University of Nottingham and AstraZeneca Research and Development Charnwood Accelerate Clinical Research of Anti-Inflammatory Drugs

The University of Nottingham, working with AstraZeneca Research and Development, needed to measure tissue oxygen saturation from hyperspectral images because conventional pulse oximeters are limited in accuracy and location of use. To develop and test algorithms and an easy-to-use analysis workflow, the research team adopted MathWorks tools—primarily MATLAB along with Image Acquisition Toolbox and Image Processing Toolbox—for image processing and algorithm development.

Using MathWorks software, the team processed 3D hyperspectral data, normalized reflectance, developed patent-pending oxygen-saturation algorithms, and built a MATLAB-based GUI for clinicians. Image Acquisition Toolbox sped image capture about threefold, development time was cut by roughly 3–4× versus C, clinical trial analysis went from months to about two weeks, and measurement accuracy improved from ~3–5% (typical fingertip oximeters) to about 0.4%. MathWorks tools continue to enable on-the-fly acquisition and analysis for ongoing studies.

University of Nottingham

Paul Rodmell

Senior Research