1. Tractometry-based Anomaly Detection for Single-subject White Matter Analysis
- Author
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Chamberland, Maxime, Genc, Sila, Raven, Erika P., Parker, Greg D., Cunningham, Adam, Doherty, Joanne, Bree, Marianne van den, Tax, Chantal M. W., and Jones, Derek K.
- Subjects
Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning - 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., Comment: Medical Imaging with Deep Learning (MIDL2020) Conference Short Paper
- Published
- 2020