14 citations · 33 across the 36 of their papers we have counts for
10 papers · 1 filter
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection
Felix Meissen, Johannes Getzner, Alexander Ziller +4
Unsupervised anomaly detection (UAD) alleviates large labeling efforts by training exclusively on unlabeled in-distribution data and detecting outliers as anomalies. Generally, the…
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…
3D Arterial Segmentation via Single 2D Projections and Depth Supervision in Contrast-Enhanced CT Images
Alina F. Dima, Veronika A. Zimmer, Martin J. Menten +8
Automated segmentation of the blood vessels in 3D volumes is an essential step for the quantitative diagnosis and treatment of many vascular diseases. 3D vessel segmentation is bei…
A skeletonization algorithm for gradient-based optimization
Martin J. Menten, Johannes C. Paetzold, Veronika A. Zimmer +6
The skeleton of a digital image is a compact representation of its topology, geometry, and scale. It has utility in many computer vision applications, such as image description, se…
Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging
Özgün Turgut, Philip Müller, Paul Hager +5
Cardiovascular diseases (CVD) can be diagnosed using various diagnostic modalities. The electrocardiogram (ECG) is a cost-effective and widely available diagnostic aid that provide…
Metrics to Quantify Global Consistency in Synthetic Medical Images
Daniel Scholz, Benedikt Wiestler, Daniel Rueckert +1
Image synthesis is increasingly being adopted in medical image processing, for example for data augmentation or inter-modality image translation. In these critical applications, th…
Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotations
Linus Kreitner, Johannes C. Paetzold, Nikolaus Rauch +11
Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality that can acquire high-resolution volumes of the retinal vasculature and aid the diagnosis of ocul…
Best of Both Worlds: Multimodal Contrastive Learning with Tabular and Imaging Data
Paul Hager, Martin J. Menten, Daniel Rueckert
Medical datasets and especially biobanks, often contain extensive tabular data with rich clinical information in addition to images. In practice, clinicians typically have less dat…
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration
Robbie Holland, Oliver Leingang, Christopher Holmes +13
Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. Current grading systems based on imaging biomarkers only coarsely group disease stages into…