S027 - 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
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.
Poster Session #3 - 9:30 - 11:00 UTC-4 (Tuesday)