Hyperspectral imaging (HSI) enables visualisation of a range of morphological and biochemical information from tissue, which could improve disease diagnostic accuracy. Unfortunately, HSI presents a substantial instrumentation challenge for biomedical applications, particularly in endoscopy where a wide range of image distortions arise that can lead to artefacts in the 3D HSI data. To address this challenge, we have developed several methods that enable the addition of HSI to endoscopic imaging, encompassing both novel sensor development, application of geometric image co-registration methods, and development of machine learning tools for rapid real-time HSI data analysis. In this presentation, I will give an overview of these advances, including our latest results from clinical studies applying HSI endoscopy in the gastrointestinal tract for early cancer detection.
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