While RGB imaging is reaching its limits, Hyperspectral Imaging (HSI) is being widely used especially for medical applications. This study points out the ability of HSI technique to help in planning the surgical procedure in orthopedic surgery by automatically identifying anatomical structures and surgical instruments thanks to their spectral signatures. Four segmentation methods have been explored: (i) average spectra method that uses the Euclidean distance between the spectrum of each pixel and the average spectrum of each specific structure, (ii) segmentation using kmeans, (iii) segmentation based on indices in which we identify reflectances ratios at specific wavelengths that allow materials to be correctly classified, (iv) and finally a pixel-based classification method based on neural networks. Experiments on anatomical objects whose physical characteristics are known to have been carried out. Selecting specific wavelengths to reduce the cost of the final device was also discussed.
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