Detection of Midline Brain Abnormalities using Convolutional Neural Networks

Aleix Solanes, Laura Igual, Joaquim Radua

Abstract:

Patients with mental diseases have an increased prevalence of abnormalities in
midline brain structures. The detection and study of these brain abnormalities in
Magnetic Resonance Imaging requires a tedious and time-consuming process of
manual image analysis. In this work, we explore, for the first time in the literature,
an automated detection method based on CNNs. In particular, we compare different
CNNs models to face this problem on a dataset of 861 subjects (639 patients with
mood or psychotic disorders and 223 healthy controls) and obtain very promising
results.

Keywords: MRI, CNN, CSP, Deep Learning, Cavum, Brain, Abnormalities

Author Affiliation: 1. FIDMAG Research Foundation, Barcelona, Spain 2. Department of Psychiatry and Forensic Medicine, Autonomous University of Barcelona, Spain 3. Department of Mathematics and Computer Science, University of Barcelona, Barcelona, Spain