Detection of Midline Brain Abnormalities using Convolutional Neural Networks

Aleix Solanes, Laura Igual, Joaquim Radua

Apr 11, 2018 (modified: May 16, 2018) MIDL 2018 Abstract Submission readers: everyone
  • 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
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