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Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
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Biomechanical modelling of brain atrophy through deep learning
We present a proof-of-concept, deep learning (DL) based, differentiable ...
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Test-time Unsupervised Domain Adaptation
Convolutional neural networks trained on publicly available medical imag...
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Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE
The increasing efficiency and compactness of deep learning architectures...
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A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality
Quality control (QC) of medical images is essential to ensure that downs...
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Let's agree to disagree: learning highly debatable multirater labelling
Classification and differentiation of small pathological objects may gre...
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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...
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Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Quantification of cerebral white matter hyperintensities (WMH) of presum...
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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...
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PIMMS: Permutation Invariant Multi-Modal Segmentation
In a research context, image acquisition will often involve a pre-define...
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Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations
Deep-learning has proved in recent years to be a powerful tool for image...
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