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Test-time Unsupervised Domain Adaptation
Convolutional neural networks trained on publicly available medical imag...
10/05/2020 ∙ by Thomas Varsavsky, et al. ∙
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Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
Labelling large datasets for training high-capacity neural networks is a...
02/16/2020 ∙ by David A. Wood, et al. ∙
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Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE
The increasing efficiency and compactness of deep learning architectures...
02/13/2020 ∙ by Petru-Daniel Tudosiu, et al. ∙
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Let's agree to disagree: learning highly debatable multirater labelling
Classification and differentiation of small pathological objects may gre...
09/04/2019 ∙ by Carole H Sudre, et al. ∙
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Improved MR to CT synthesis for PET/MR attenuation correction using Imitation Learning
The ability to synthesise Computed Tomography images - commonly known as...
08/21/2019 ∙ by Kerstin Kläser, et al. ∙
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Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning
Supervised learning algorithms trained on medical images will often fail...
08/16/2019 ∙ by Mauricio Orbes-Arteaga, et al. ∙
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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...
07/25/2019 ∙ by Zach Eaton-Rosen, et al. ∙
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3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects
Extremely small objects (ESO) have become observable on clinical routine...
12/21/2018 ∙ by Carole H Sudre, et al. ∙
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PIMMS: Permutation Invariant Multi-Modal Segmentation
In a research context, image acquisition will often involve a pre-define...
07/17/2018 ∙ by Thomas Varsavsky, et al. ∙
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