1 citations · 1 across the 3 of their papers we have counts for
3 papers
MO-CTranS: A unified multi-organ segmentation model learning from multiple heterogeneously labelled datasets
Zhendi Gong, Susan Francis, Eleanor Cox +5
Multi-organ segmentation holds paramount significance in many clinical tasks. In practice, compared to large fully annotated datasets, multiple small datasets are often more access…
An Attentive Representative Sample Selection Strategy Combined with Balanced Batch Training for Skin Lesion Segmentation
Stephen Lloyd-Brown, Susan Francis, Caroline Hoad +4
An often overlooked problem in medical image segmentation research is the effective selection of training subsets to annotate from a complete set of unlabelled data. Many studies s…
Mixed Effect Modelling of Single Trial Variability in Ultra-High Field fMRI
Christopher J. Brignell, William J. Browne, Ian L. Dryden +1
Neuronal brain activity in response to repeated stimuli can be perceived using functional magnetic resonance imaging (fMRI). In this paper, we develop a statistical model for fMRI…