5 citations · 19 across the 20 of their papers we have counts for
10 papers · 1 filter
Fast Predictive Simple Geodesic Regression
Zhipeng Ding, Greg Fleishman, Xiao Yang +3
Deformable image registration and regression are important tasks in medical image analysis. However, they are computationally expensive, especially when analyzing large-scale datas…
Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
Nikita Mokrov, Maxim Panov, Boris A. Gutman +3
This paper considers the problem of brain disease classification based on connectome data. A connectome is a network representation of a human brain. The typical connectome classif…
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…
Identifying Genetic Risk Factors via Sparse Group Lasso with Group Graph Structure
Tao Yang, Paul Thompson, Sihai Zhao +1
Genome-wide association studies (GWA studies or GWAS) investigate the relationships between genetic variants such as single-nucleotide polymorphisms (SNPs) and individual traits. R…
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…
Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification
Dmitry Petrov, Alexander Ivanov, Joshua Faskowitz +5
There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to disting…