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02/23/2022
Augmentation based unsupervised domain adaptation
The insertion of deep learning in medical image analysis had lead to the...
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11/07/2021
Acquisition-invariant brain MRI segmentation with informative uncertainties
Combining multi-site data can strengthen and uncover trends, but is a ta...
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11/04/2021
The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
Being able to adequately process and combine data arising from different...
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10/05/2020
Test-time Unsupervised Domain Adaptation
Convolutional neural networks trained on publicly available medical imag...
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02/16/2020
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
Labelling large datasets for training high-capacity neural networks is a...
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02/13/2020
Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE
The increasing efficiency and compactness of deep learning architectures...
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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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08/21/2019
Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning
The ability to synthesise Computed Tomography images - commonly known as...
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08/16/2019
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning
Supervised learning algorithms trained on medical images will often fail...
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07/25/2019
As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging
Counting is a fundamental task in biomedical imaging and count is an imp...
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12/21/2018
3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects
Extremely small objects (ESO) have become observable on clinical routine...
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07/17/2018