Detection of Dementia Through 3D Convolutional Neural Networks Based on Amyloid PET

Abstract

Dementia is one of the most common diseases in the elderly and a leading cause of mortality and disability. In recent years, a research effort has been made to develop computer aided diagnosis tools based on machine (deep) learning models fed with neuroimaging data. However, while much work has been done on MRI imaging, very little attention has been paid on amyloid PETs, which have been recently recognized to be a promising and powerful biomarker of neurodegeneration. In this paper, we contribute to this less explored research area by proposing a 3D Convolutional Neural Network aimed at detecting dementia based on amyloid PET scans. An experiment performed on the recently released OASIS-3 dataset, which provides the community with a new benchmark to advance this line of research further, yielded very promising results and provided new evidence on the effectiveness of amyloid PET.