activity
20162026
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 3.9k across the 134 of their papers we have counts for

collaborators
Showing 2024Show all

31 papers · 1 filter

physics.med-ph2024

A Lightweight Optimization Framework for Estimating 3D Brain Tumor Infiltration

Jonas Weidner, Michal Balcerak, Ivan Ezhov +6

Glioblastoma, the most aggressive primary brain tumor, poses a severe clinical challenge due to its diffuse microscopic infiltration, which remains largely undetected on standard M…

cs.CV2024★ 2 cited

Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learning

Francesco Girlanda, Olga Demler, Bjoern Menze +1

Accurate prediction of cardiovascular diseases remains imperative for early diagnosis and intervention, necessitating robust and precise predictive models. Recently, there has been…

cs.CV2024

Predicting Stroke through Retinal Graphs and Multimodal Self-supervised Learning

Yuqing Huang, Bastian Wittmann, Olga Demler +2

Early identification of stroke is crucial for intervention, requiring reliable models. We proposed an efficient retinal image representation together with clinical information to c…

eess.IV2024

vesselFM: A Foundation Model for Universal 3D Blood Vessel Segmentation

Bastian Wittmann, Yannick Wattenberg, Tamaz Amiranashvili +2

Segmenting 3D blood vessels is a critical yet challenging task in medical image analysis. This is due to significant imaging modality-specific variations in artifacts, vascular pat…

cs.CV2024★ 1 cited

Advancing Stroke Risk Prediction Using a Multi-modal Foundation Model

Camille Delgrange, Olga Demler, Samia Mora +3

Predicting stroke risk is a complex challenge that can be enhanced by integrating diverse clinically available data modalities. This study introduces a self-supervised multimodal f…

cs.CV2024

Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization

Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner +7

Physical models in the form of partial differential equations serve as important priors for many under-constrained problems. One such application is tumor treatment planning, which…