How hyperspectral imaging and artificial intelligence transform Alzheimer's diagnosis

Abstract

In a recent multidisciplinary study involving 39 patients, the potential of retinal imaging techniques for the diagnosis of Alzheimer's disease was investigated. An easy-to-use hyperspectral snapshot camera - 16 spectral bands between 460 nm and 620 nm with 10nm bandwidth - was used to quantify amyloid accumulation, while optical coherence tomography allowed the thickness of the retinal nerve fibre layer to be assessed. Dedicated image preprocessing and machine learning were instrumental in discriminating between Alzheimer patients and healthy subjects. The best results were obtained when the hyperspectral and OCT data were combined.