Tractometry-based Anomaly Detection for Single-subject White Matter Analysis

Maxime Chamberland, Sila Genc, Erika P. Raven, Greg D. Parker, Adam Cunningham, Joanne Doherty, Marianne van den Bree, Chantal M. W. Tax, Derek K. Jones

Keywords: Diffusion MRI, Tractography, Tractometry, Anomaly Detection, Autoencoder

TL;DR: We present a framework to learn normative microstructural brain features derived from diffusion MRI Tractometry for anomaly detection.

Track: short paper

Paper Type: both

Abstract: There is an urgent need for a paradigm shift from group-wise comparisons to individual diagnosis in diffusion MRI (dMRI) to enable the analysis of rare cases and clinically-heterogeneous groups. Deep autoencoders have shown great potential to detect anomalies in neuroimaging data. We present a framework that operates on the manifold of white matter (WM) pathways to learn normative microstructural features, and discriminate those at genetic risk from controls in a paediatric population.

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