1.2k citations
- Technical University of MunichDE99 papers
- Imperial College LondonGB36 papers
- Helmholtz MunichDE21 papers
- University of ZurichCH16 papers
- Ludwig-Maximilians-Universität MünchenDE12 papers
- Johns Hopkins UniversityUS11 papers
- Harvard UniversityUS10 papers
- Heidelberg UniversityDE10 papers
- Radboud University Medical CenterNL10 papers
- Radboud University NijmegenNL10 papers
- Deutsches Herzzentrum MünchenDE9 papers
- King's College LondonGB9 papers
18 papers · 1 filter
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs
Taha Emre, Arunava Chakravarty, Antoine Rivail +10
Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent famil…
Evaluation of GPT-4 for chest X-ray impression generation: A reader study on performance and perception
Sebastian Ziegelmayer, Alexander W. Marka, Nicolas Lenhart +7
The remarkable generative capabilities of multimodal foundation models are currently being explored for a variety of applications. Generating radiological impressions is a challeng…
From Text to Image: Exploring GPT-4Vision's Potential in Advanced Radiological Analysis across Subspecialties
Felix Busch, Tianyu Han, Marcus Makowski +3
The study evaluates and compares GPT-4 and GPT-4Vision for radiological tasks, suggesting GPT-4Vision may recognize radiological features from images, thereby enhancing its diagnos…
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik +5
Uncertainty estimation, which provides a means of building explainable neural networks for medical imaging applications, have mostly been studied for single deep learning models th…
APIS: A paired CT-MRI dataset for ischemic stroke segmentation challenge
Santiago Gómez, Daniel Mantilla, Gustavo Garzón +4
Stroke is the second leading cause of mortality worldwide. Immediate attention and diagnosis play a crucial role regarding patient prognosis. The key to diagnosis consists in local…
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
Nicolas Schischka, Hannah Schieber, Mert Asim Karaoglu +6
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines…