69 citations · 217 across the 36 of their papers we have counts for
3 papers · 1 filter
The Data Manifold under the Microscope
Marios Koulakis, Constantin Seibold
A significant gap exists between theory and practice in deep learning. Generalization and approximation error bounds are often derived for simplified models or are too loose to be…
The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization
Jakob Dexl, Katharina Jeblick, Andreas Mittermeier +27
We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body PET/CT under a compositional generaliza…
Region-Normalized DPO for Medical Image Segmentation under Noisy Judges
Hamza Kalisch, Constantin Seibold, Jens Kleesiek +2
While dense pixel-wise annotations remain the gold standard for medical image segmentation, they are costly to obtain and limit scalability. In contrast, many deployed systems alre…