Alzheimer's disease diagnostics by a deeply supervised adaptable 3D convolutional network

Abstract

Early diagnosis, playing an important role in preventing progress and treating the Alzheimer's disease (AD), is based on classification of features extracted from brain images. The features have to accurately capture main AD-related variations of anatomical brain structures, such as, eg, ventricles size, hippocampus shape, cortical thickness, and brain volume.