论文标题
基于术法的异常检测，用于单对象白质分析
Tractometry-based Anomaly Detection for Single-subject White Matter Analysis
论文作者
论文摘要
迫切需要从范围的比较到扩散MRI（DMRI）的个体诊断以实现罕见病例和临床杂种组的分析。深度自动编码器显示出在神经影像数据中检测异常情况的巨大潜力。我们提出了一个框架，该框架以白质（WM）途径的流动方式运作，以学习规范性微结构特征，并区分那些在儿科人群中控制遗传风险的人。
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.
