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Tractometry-based Anomaly Detection for Single-subject White Matter Analysis
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Paper
Tractometry-based Anomaly Detection for Single-subject White Matter Analysis
2020
Overview
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.
Publisher
Cornell University Library, arXiv.org
Subject
