Riemannian Metric Learning for Progression Modeling of Longitudinal Datasets
2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)(2022)
摘要
Explicit descriptions of the progression of biomarkers across time usually involve priors on the shapes of the trajectories. To circumvent this limitation, we propose a geometric framework to learn a manifold representation of longitudinal data. Namely, we introduce a family of Riemannian metrics that span a set of curves defined as parallel variations around a main geodesic, and apply that framew...
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关键词
Measurement,Manifolds,Shape,Biological system modeling,Biomarkers,Data models,Trajectory
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