A novel Convolutional Neural Network Model Based on Voxel-based Morphometry of Imaging Data in Predicting the Prognosis of Patients with Mild Cognitive Impairment

Objective: Nowadays, it is of great interest to identify neuroimaging biomarkers for the early detection of Alzheimer's disease (AD). It is considered that approximately half of patients with a diagnosis of mild cognitive impairment (MCI) eventually develop Alzheimer's disease, and the other half remain stable. In this context, a novel convolutional neural network (CNN) based on voxel-based morphometric analysis is proposed to predict the prognosis of patients with MCI using their baseline structural magnetic resonance (MR) images.