16 citations · 44 across the 9 of their papers we have counts for
10 papers
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
Zhijian Yang, Junhao Wen, Ahmed Abdulkadir +25
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multipl…
BAyesian Bent-Line Regression model for longitudinal data with an application to the study of cognitive performance trajectories in Wisconsin Registry for Alzheimer's Prevention
Lianlian Du, Rebecca Langhough Koscik, Tobey J Betthauser +3
Preclinical Alzheimer's disease (AD), the earliest stage in the AD continuum, can last fifteen to twenty years, with cognitive decline trajectories nonlinear and heterogeneous betw…
Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging
Vishnu M. Bashyam, Jimit Doshi, Guray Erus +24
Conventional and deep learning-based methods have shown great potential in the medical imaging domain, as means for deriving diagnostic, prognostic, and predictive biomarkers, and…
Online Graph Completion: Multivariate Signal Recovery in Computer Vision
Won Hwa Kim, Mona Jalal, Seongjae Hwang +2
The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision)…
DUAL-GLOW: Conditional Flow-Based Generative Model for Modality Transfer
Haoliang Sun, Ronak Mehta, Hao H. Zhou +4
Positron emission tomography (PET) imaging is an imaging modality for diagnosing a number of neurological diseases. In contrast to Magnetic Resonance Imaging (MRI), PET is costly a…
Finding Differentially Covarying Needles in a Temporally Evolving Haystack: A Scan Statistics Perspective
Ronak Mehta, Hyunwoo J. Kim, Shulei Wang +3
Recent results in coupled or temporal graphical models offer schemes for estimating the relationship structure between features when the data come from related (but distinct) longi…