22 citations · 53 across the 22 of their papers we have counts for
4 papers · 1 filter
nnInteractive Agent: General-Purpose AI Agents as 3D Image Annotators
Fabian Isensee, Constantin Ulrich Harsy, Maximilian Rokuss +3
Interactive 3D segmentation models such as nnInteractive turn a few spatial prompts (points, scribbles, boxes) into accurate volumetric masks, but a human still does the annotation…
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation
Tristan Kirscher, Markus Bujotzek, Yannick Kirchhoff +5
Ensemble disagreement is widely used as a proxy for epistemic uncertainty in medical image segmentation. In practice, many studies form ensembles via K-fold cross-validation (CV),…
Finally Outshining the Random Baseline: A Simple and Effective Solution for Active Learning in 3D Biomedical Imaging
Carsten T. Lüth, Jeremias Traub, Kim-Celine Kahl +6
Active learning (AL) has the potential to drastically reduce annotation costs in 3D biomedical image segmentation, where expert labeling of volumetric data is both time-consuming a…