3 citations · 4 across the 6 of their papers we have counts for
6 papers
Evaluation of Uncertainty-Aware Multi-Software Ensembles for Hippocampal Segmentation
Gabriel Oliveira-Stahl, Anna Schroder, James Moggridge +6
Accurate hippocampal segmentation can be a useful tool for diagnosing and monitoring neurological conditions such as Alzheimer's disease and epilepsy. While numerous automated segm…
LLM enhanced graph inference for long-term disease progression modelling
Tiantian He, An Zhao, Elinor Thompson +4
Understanding the interactions between biomarkers among brain regions during neurodegenerative disease is essential for unravelling the mechanisms underlying disease progression. F…
Connectomics Informed by Large Language Models
Elinor Thompson, Tiantian He, Anna Schroder +5
Tractography is a unique method for mapping white matter connections in the brain, but tractography algorithms suffer from an inherent trade-off between sensitivity and specificity…
A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
Tiantian He, Keyue Jiang, An Zhao +5
The long-term progression of neurodegenerative diseases is commonly conceptualized as a spatiotemporal diffusion process that consists of a graph diffusion process across the struc…
A coupled-mechanisms modelling framework for neurodegeneration
Tiantian He, Elinor Thompson, Anna Schroder +4
Computational models of neurodegeneration aim to emulate the evolving pattern of pathology in the brain during neurodegenerative disease, such as Alzheimer's disease. Previous stud…
Rician likelihood loss for quantitative MRI using self-supervised deep learning
Christopher S. Parker, Anna Schroder, Sean C. Epstein +3
Purpose: Previous quantitative MR imaging studies using self-supervised deep learning have reported biased parameter estimates at low SNR. Such systematic errors arise from the cho…