6 citations · 15 across the 13 of their papers we have counts for
7 papers · 1 filter
Geometric Modeling of Hippocampal Tau Deposition: A Surface-Based Framework for Covariate Analysis and Off-Target Contamination Detection
Liangkang Wang, Akhil Ambekar, Ani Eloyan
We introduce a framework combining geometric modeling with disease progression analysis to investigate tau deposition in Alzheimer's disease (AD) using positron emission tomography…
Longitudinal Principal Manifold Estimation
Robert Zielinski, Kun Meng, Ani Eloyan
Longitudinal magnetic resonance imaging data is used to model trajectories of change in brain regions of interest to identify areas susceptible to atrophy in those with neurodegene…
Leveraging population information in brain connectivity via Bayesian ICA with a novel informative prior for correlation matrices
Amanda Mejia, David Bolin, Daniel Spencer +1
Brain functional connectivity (FC), the temporal synchrony between brain networks, is essential to understand the functional organization of the brain and to identify changes due t…
Brain Functional Connectivity Estimation Utilizing Diffusion Kernels on a Structural Connectivity Graph
Nathan Tung, Jerome Sanes, Eli Upfal +1
Functional connectivity (FC) refers to the investigation of interactions between brain regions to understand integration of neural activity in several regions. FC is often estimate…
Population-level Task-evoked Functional Connectivity via Fourier Analysis
Kun Meng, Ani Eloyan
Functional magnetic resonance imaging (fMRI) is a non-invasive and in-vivo imaging technique essential for measuring brain activity. Functional connectivity is used to study associ…
Relating multi-sequence longitudinal intensity profiles and clinical covariates in new multiple sclerosis lesions
Elizabeth M. Sweeney, Russell T. Shinohara, Blake E. Dewey +5
Structural magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients. The formation of these lesions is a complex process inv…
Homotopic Group ICA for Multi-Subject Brain Imaging Data
Juemin Yang, Ani Eloyan, Anita Barber +5
Independent Component Analysis (ICA) is a computational technique for revealing latent factors that underlie sets of measurements or signals. It has become a standard technique in…