research
∙
05/02/2023
Expectation Maximization Pseudo Labelling for Segmentation with Limited Annotations
We study pseudo labelling and its generalisation for semi-supervised seg...
share
research
∙
08/08/2022
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation
This paper concerns pseudo labelling in segmentation. Our contribution i...
research
∙
10/23/2021
MisMatch: Learning to Change Predictive Confidences with Attention for Consistency-Based, Semi-Supervised Medical Image Segmentation
The lack of labels is one of the fundamental constraints in deep learnin...
research
∙
12/28/2020
Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration
This work presents a single-step deep-learning framework for longitudina...
research
∙
05/26/2020
Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging
Subtle changes in white matter (WM) microstructure have been associated ...
research
∙
08/26/2019
Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset
Tract-specific diffusion measures, as derived from brain diffusion MRI, ...
research
∙
08/26/2019
A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes
To accurately analyze changes of anatomical structures in longitudinal i...
research
∙
07/01/2019