D. Rueckert

Latest

Evaluating Normative Representation Learning in Generative AI for Robust Anomaly Detection in Brain Imaging.
Metadata-enhanced contrastive learning from retinal optical coherence tomography images.
Reconciling privacy and accuracy in AI for medical imaging.
Evaluation and mitigation of the limitations of large language models in clinical decision-making.
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art.
Federated electronic health records for the European Health Data Space.
A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks.
Interactive and Explainable Region-guided Radiology Report Generation.
Concurrent ischemic lesion age estimation and segmentation of CT brain using a Transformer-based network.
DeepMesh: Mesh-based Cardiac Motion Tracking using Deep Learning.
Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging.
Differentially Private Graph Neural Networks for Whole-Graph Classification.
Best of Both Worlds: Multimodal Contrastive Learning With Tabular and Imaging Data.
Causality-inspired Single-source Domain Generalization for Medical Image Segmentation.
Enhancing MR image segmentation with realistic adversarial data augmentation.
Generative myocardial motion tracking via latent space exploration with biomechanics-informed prior.
Self-supervised Learning for Few-shot Medical Image Segmentation.
The Developing Human Connectome Project Neonatal Data Release.
Adversarial interference and its mitigations in privacy-preserving collaborative machine learning.
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies with Progress Highlights, and Future Promises.
Federated deep learning for detecting COVID-19 lung abnormalities in CT: A privacy-preserving multinational validation study.