5 citations · 19 across the 20 of their papers we have counts for
6 papers · 1 filter
Overview of Scanner Invariant Representations
Daniel Moyer, Greg Ver Steeg, Paul M. Thompson
Pooled imaging data from multiple sources is subject to bias from each source. Studies that do not correct for these scanner/site biases at best lose statistical power, and at wors…
Scanner Invariant Representations for Diffusion MRI Harmonization
Daniel Moyer, Greg Ver Steeg, Chantal M. W. Tax +1
Purpose: In the present work we describe the correction of diffusion-weighted MRI for site and scanner biases using a novel method based on invariant representation. Theory and Met…
Measures of Tractography Convergence
Daniel Moyer, Paul M. Thompson, Greg Ver Steeg
In the present work, we use information theory to understand the empirical convergence rate of tractography, a widely-used approach to reconstruct anatomical fiber pathways in the…
A Fast, Accurate Two-Step Linear Mixed Model for Genetic Analysis Applied to Repeat MRI Measurements
Qifan Yang, Gennady V. Roshchupkin, Wiro J. Niessen +4
Large-scale biobanks are being collected around the world in efforts to better understand human health and risk factors for disease. They often survey hundreds of thousands of indi…
Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging
Dmitry Petrov, Boris A. Gutman, Shih-Hua +72
As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts ha…
The Importance of Being Negative: A serious treatment of non-trivial edges in brain functional connectome
Liang Zhan, Lisanne M. Jenkins, Ouri E. Wolfson +6
Understanding the modularity of fMRI-derived brain networks or connectomes can inform the study of brain function organization. However, fMRI connectomes additionally involve negat…