Math Biology Seminar
Hyperspectral imaging is a powerful tool that adds quantitative spectral information as the third dimension for each pixel, thus overcoming this limitation. However, there is a high demand for data analysis approaches to extract useful spectral-spatial information from the complex tissues of the eye and other tissues in 3D hyperspectral images. To address this need, we develop open-source 3D segmentation algorithms that can effectively extract spectral-spatial information from hyperspectral images of eye tissues. These algorithms can also be expanded to analyze hyperspectral images of other tissues.