UNSURE 2020
Image registration via stochastic gradient Markov chain Monte Carlo
RevPHiSeg: A Memory-Efficient Neural Network for Uncertainty Quantification
Hierarchical brain parcellation with uncertainty
Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-Class Segmentation
Uncertainty Estimation in Landmark Localization based on Gaussian Heatmaps
Weight averaging impact on the uncertainty of retinal artery-venous segmentation
Improving Pathological Distribution Measurements with Bayesian Uncertainty
Improving Reliability of Clinical Models using Prediction Calibration
Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior
Uncertainty Estimation for Assessment of 3D US Scan Adequacy and DDH Metric Reliability
GRAIL 2020
Clustering-based Deep Brain MultiGraph Integrator Network for Learning Connectional Brain Templates
Detection of Discriminative Neurological Circuits Using Hierarchical Graph Convolutional Networks in fMRI Sequences
Graph Matching Based Connectomic Biomarker with Learning for Brain Disorders
Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Proling
Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation
Min-cut Max-flow for Network Abnormality Detection: Application to Preterm Birth
Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification
Intraoperative Liver Surface Completion with Graph Convolutional VAE
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification.