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Results for: Publications | Neuroimage-based Phenotyping Project


On training deep 3D CNN models with dependent samples in neuroimaging. Xiong Y, Kim HJ, Tangirala B, Mehta R, Johnson S, Singh V. Proceedings of the International Conference on Information Processing in Medical Imaging, 2019.

Localizing differentially evolving covariance structures via scan statistics. Mehta R, Kim HJ, Wang S, Johnson S, Yuan M, Singh V. Quarterly of Applied Mathematics 77:357-398, 2019.

A natural language interface for dissemination of reproducible biomedical data science. John RJL, Patel J, Alexander A, Singh V, Adluru N. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 197-205.

Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Zhou HH, Singh V, Johnson SC, Wahba G, and the Alzheimer’s Disease Neuroimaging Initiative. Proceedings of the National Academy of Sciences USA, 2018.

A geometric framework for statistical analysis of trajectories with distinct temporal spans. Chakraborty R, Singh V, Adluru N, Vemuri B. Proceedings of the International Conference on Computer Vision (ICCV), 2017.

Accelerating permutation testing in voxel-wise analysis through subspace tracking: A new plugin for SnPM. Gutierrez-Barragan F, Ithapu VK, Hinrichs C, Maumet C, Johnson SC, Nichols TE, Singh V. Neuroimage 159(1):79-98, 2017.

Modeling cognitive trends in preclinical Alzheimer's disease (AD) via distributions over permutations. Plumb G, Clark LR, Johnson SC, Singh V. Proceedings of Medical Image Computing And Computer Assisted Intervention (MICCAI), 2017.

When can multi-site datasets be pooled for regression? Hypothesis tests, L2-consistency and neuroscience applications. Zhou HH, Zhang Y, Ithapu VK, Johnson SC, Wahba G, Singh V. Proceedings of the International Conference on Machine Learning (ICML), 2017.

Riemannian nonlinear mixed effects models: analyzing longitudinal deformations in neuroimaging. Kim HJ, Adluru N, Suri H, Vemuri BC, Johnson SC, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

Riemannian variance filtering: An independent filtering scheme for statistical tests on manifold-valued data. Zheng L, Kim HJ, Adluru N, Newton MA, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017.

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