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Found 2 papers, 1 papers with code
A Spectral Library and Method for Sparse Unmixing of Hyperspectral Images in Fluorescence Guided Resection of Brain Tumors
With this knowledge, we introduce (1) a library of 9 endmember spectra, (2) a sparse, non-negative Poisson regression algorithm to perform physics-informed unmixing with this library without overfitting, and (3) a highly realistic spectral measurement simulation with known endmember abundances.
Towards Machine Learning-based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection
For tissue type, at least four of the five fluorophore abundances were found to be significantly different (p < 0. 01) between all classes.
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