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10/08/2021
Is MC Dropout Bayesian?
MC Dropout is a mainstream "free lunch" method in medical imaging for ap...
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08/11/2021
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
Using publicly available data to determine the performance of methodolog...
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08/10/2021
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data
Convolutional Neural Networks (CNNs) are widely used for image classific...
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07/31/2021
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
Datasets are rarely a realistic approximation of the target population. ...
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08/13/2020
Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface
Accurate estimation of the age in neonates is essential for measuring ne...
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06/10/2020
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
In image segmentation, there is often more than one plausible solution f...
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06/28/2019
Explainable Shape Analysis through Deep Hierarchical Generative Models: Application to Cardiac Remodeling
Quantification of anatomical shape changes still relies on scalar global...
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03/06/2019
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing
We investigate discrete spin transformations, a geometric framework to m...
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03/05/2019
FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
We present a new approach to diffeomorphic non-rigid registration of med...
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06/08/2018
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents
We propose a fully automatic method to find standardized view planes in ...
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06/07/2018
Semi-Supervised Learning via Compact Latent Space Clustering
We present a novel cost function for semi-supervised learning of neural ...
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04/11/2018