5 citations · 19 across the 20 of their papers we have counts for
24 papers
3D Grid-Attention Networks for Interpretable Age and Alzheimer's Disease Prediction from Structural MRI
Pradeep Lam, Alyssa H. Zhu, Iyad Ba Gari +2
We propose an interpretable 3D Grid-Attention deep neural network that can accurately predict a person's age and whether they have Alzheimer's disease (AD) from a structural brain…
Deep Representation Learning For Multimodal Brain Networks
Wen Zhang, Liang Zhan, Paul Thompson +1
Applying network science approaches to investigate the functions and anatomy of the human brain is prevalent in modern medical imaging analysis. Due to the complex network topology…
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…
Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data
Santiago Silva, Boris Gutman, Eduardo Romero +3
At this moment, databanks worldwide contain brain images of previously unimaginable numbers. Combined with developments in data science, these massive data provide the potential to…
Deep Learning for Quality Control of Subcortical Brain 3D Shape Models
Dmitry Petrov, Boris A. Gutman Egor Kuznetsov, Theo G. M. van Erp +70
We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional ne…