ArticleProceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition2017
Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging.
Article in Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Shape modeling of longitudinal medical images: from diffeomorphic metric mapping to deep learning.Frontiers in artificial intelligence · 2025Review
- Modeling Longitudinal Optical Coherence Tomography Images for Monitoring and Analysis of Glaucoma Progression.Shape in medical imaging : International Workshop, ShapeMI 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. ShapeMI (Workshop) (2023 : Vancouver, B.C.) · 2023Article
- Hierarchical geodesic modeling on the diffusion orientation distribution function for longitudinal DW-MRI analysis.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2020Article
- Statistical model for dynamically-changing correlation matrices with application to brain connectivity.Journal of neuroscience methods · 2020Review
- Hierarchical Multi-Geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019Article
- On Training Deep 3D CNN Models with Dependent Samples in Neuroimaging.Information processing in medical imaging : proceedings of the ... conference · 2019Article
- A Riemannian Framework for Longitudinal Analysis of Resting-State Functional Connectivity.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2018Article
- A Natural Language Interface for Dissemination of Reproducible Biomedical Data Science.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2018Article
- A geometric framework for statistical analysis of trajectories with distinct temporal spans.Proceedings. IEEE International Conference on Computer Vision · 2017Article
- Dilated Convolutional Neural Networks for Sequential Manifold-valued Data.Proceedings. IEEE International Conference on Computer VisionArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Statistical machine learning models that operate on manifold-valued data are being extensively studied in vision, motivated by applications in activity recognition, feature tracking and medical imaging. While non-parametric methods have been relatively well studied in the literature, efficient formulations for parametric models (which may offer benefits in small sample size regimes) have only emerged recently. So far, manifold-valued regression models (such as geodesic regression) are restricted to the analysis of cross-sectional data, i.e., the so-called "fixed effects" in statistics. But in most "longitudinal analysis" (e.g., when a participant provides multiple measurements, over time) the application of fixed effects models is problematic. In an effort to answer this need, this paper generalizes non-linear mixed effects model to the regime where the response variable is manifold-valued, i.e., f :
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.