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
∙
10/17/2022
Deformably-Scaled Transposed Convolution
Transposed convolution is crucial for generating high-resolution outputs...
research
∙
08/30/2022
Airway measurement by refinement of synthetic images improves mortality prediction in idiopathic pulmonary fibrosis
Several chronic lung diseases, like idiopathic pulmonary fibrosis (IPF) ...
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
∙
03/19/2022
Learning Morphological Feature Perturbations for Calibrated Semi-Supervised Segmentation
We propose MisMatch, a novel consistency-driven semi-supervised segmenta...
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
∙
07/31/2020
Disentangling Human Error from the Ground Truth in Segmentation of Medical Images
Recent years have seen increasing use of supervised learning methods for...
research
∙
07/29/2020
