CUVIS.AI: a new open source platform and three state-of-the-art applications of machine learning in hyperspectral imaging

René Heine; Robert Briegel; Arnd Brandes; Ben Müller; Barbara Darnell

doi:10.1117/12.2685302

20 October 2023 CUVIS.AI: a new open source platform and three state-of-the-art applications of machine learning in hyperspectral imaging

René Heine, Robert Briegel, Arnd Brandes, Ben Müller, Barbara Darnell

Author Affiliations +

Proceedings Volume 12688, Imaging Spectrometry XXVI: Applications, Sensors, and Processing; 1268805 (2023) https://doi.org/10.1117/12.2685302
Event: SPIE Optical Engineering + Applications, 2023, San Diego, California, United States

Abstract

Hyperspectral imaging (HSI) is a technique that reveals hidden information that cannot be seen by the human eye or conventional cameras. However, HSI also poses many challenges such as high data dimensionality, complex signal processing and interpretation, and expensive hardware and software requirements. cuvis.ai is a new open source platform and scientific community that aims to make HSI more accessible, affordable and applicable for everyone. cuvis.ai leverages the power of modern AI concepts to unleash the full potential of HSI. We demonstrate the usefulness of cuvis.ai with three state-of-the-art applications of machine learning in HSI: detecting Alzheimer’s disease, providing surgical guidance, and diagnosing melanoma.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

René Heine, Robert Briegel, Arnd Brandes, Ben Müller, and Barbara Darnell "CUVIS.AI: a new open source platform and three state-of-the-art applications of machine learning in hyperspectral imaging", Proc. SPIE 12688, Imaging Spectrometry XXVI: Applications, Sensors, and Processing, 1268805 (20 October 2023); https://doi.org/10.1117/12.2685302

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