60 citations · 353 across the 40 of their papers we have counts for
7 papers · 1 filter
Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures
Eloy Geenjaar, Tonya White, Vince Calhoun
We propose to apply non-linear representation learning to voxelwise rs-fMRI data. Learning the non-linear representations is done using a variational autoencoder (VAE). The VAE is…
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data
Alex Fedorov, Eloy Geenjaar, Lei Wu +3
Self-supervised learning has enabled significant improvements on natural image benchmarks. However, there is less work in the medical imaging domain in this area. The optimal model…
Causality based Feature Fusion for Brain Neuro-Developmental Analysis
Peyman Hosseinzadeh Kassani, Li Xiao, Gemeng Zhang +4
Human brain development is a complex and dynamic process that is affected by several factors such as genetics, sex hormones, and environmental changes. A number of recent studies o…
Learnt dynamics generalizes across tasks, datasets, and populations
U. Mahmood, M. M. Rahman, A. Fedorov +3
Differentiating multivariate dynamic signals is a difficult learning problem as the feature space may be large yet often only a few training examples are available. Traditional app…
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR
Alvaro Ulloa, Sergey Plis, Vince Calhoun
The wide variety of brain imaging technologies allows us to exploit information inherent to different data modalities. The richness of multimodal datasets may increase predictive p…
Almost instant brain atlas segmentation for large-scale studies
Alex Fedorov, Eswar Damaraju, Vince Calhoun +1
Large scale studies of group differences in healthy controls and patients and screenings for early stage disease prevention programs require processing and analysis of extensive mu…