Abstract
Neurocognitive disorders (NCD) affect over 50 million people globally. The detection biomarkers using brain imaging or cerebrospinal fluid are expensive procedures. Blood-based biomarkers such as plasma or serum present a cost-effective alternative. The work presented in this paper is focused on the use of hyperspectral (HS) imaging (HSI) to classify plasma samples in order to discriminate between patients with major NCD and healthy control subjects. HS images of plasma samples were obtained using a SWIR (Short-Wave Infrared) camera able to capture 273 bands within the 900-2,500 nm spectral range. A preliminary HSI database was obtained with 20 major NCD samples and 20 control samples. This data was segmented and classified using pixel-wise supervised classification algorithms, achieving 75% sensitivity and 100% specificity results with the best classifier in the test set.
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