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04/26/2023
Low-field magnetic resonance image enhancement via stochastic image quality transfer
Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in wide...
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07/11/2022
Repairing Neural Networks by Leaving the Right Past Behind
Prediction failures of machine learning models often arise from deficien...
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09/25/2021
A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging
Machine learning models commonly exhibit unexpected failures post-deploy...
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09/22/2021
Learning to Downsample for Segmentation of Ultra-High Resolution Images
Segmentation of ultra-high resolution images with deep learning is chall...
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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...
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07/29/2020
Foveation for Segmentation of Ultra-High Resolution Images
Segmentation of ultra-high resolution images is challenging because of t...
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03/16/2020
Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients
1.5T or 3T scanners are the current standard for clinical MRI, but low-f...
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09/16/2019
Reproducibility of an airway tapering measurement in CT with application to bronchiectasis
Purpose: This paper proposes a pipeline to acquire a scalar tapering mea...
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09/15/2019
Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator
MR images scanned at low magnetic field (<1T) have lower resolution in t...
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09/14/2019
Tapering Analysis of Airways with Bronchiectasis
Bronchiectasis is the permanent dilation of airways. Patients with the d...
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09/04/2019
Let's agree to disagree: learning highly debatable multirater labelling
Classification and differentiation of small pathological objects may gre...
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08/26/2019
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
The performance of multi-task learning in Convolutional Neural Networks ...
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07/31/2019
Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement
Deep learning (DL) has shown great potential in medical image enhancemen...
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07/26/2019
Multi-Stage Prediction Networks for Data Harmonization
In this paper, we introduce multi-task learning (MTL) to data harmonizat...
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06/28/2019
Modelling Airway Geometry as Stock Market Data using Bayesian Changepoint Detection
Numerous lung diseases, such as idiopathic pulmonary fibrosis (IPF), exh...
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02/10/2019
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion
The predictive performance of supervised learning algorithms depends on ...
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08/16/2018
Deeper Image Quality Transfer: Training Low-Memory Neural Networks for 3D Images
In this paper we address the memory demands that come with the processin...
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07/17/2018
Adaptive Neural Trees
Deep neural networks and decision trees operate on largely separate para...
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06/18/2018
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Multi-task neural network architectures provide a mechanism that jointly...
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06/07/2018