Deep Learning for Mental Illness Detection Using Brain SPECT Imaging

Abstract

We apply deep learning to the detection of mental illness with meaningful results, using SPECT (Single Photon Emission Computed Tomography) images of the brain. The data consists in scans from patients with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD) and obsessive compulsive disorder (OCD), plus scans of healthy brains. We focus here on the application of a deep convolutional neural network (CNN). The main challenge in using CNN models for medical diagnosis is often the number of samples not being sufficiently large to ensure high accuracy. We propose a soft classifier for using the machine. Instead of a binary output “yes/no” for each condition, we add a..