1 citations · 2 across the 4 of their papers we have counts for
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Navigating Uncertainty in Medical Image Segmentation
Kilian Zepf, Jes Frellsen, Aasa Feragen
We address the selection and evaluation of uncertain segmentation methods in medical imaging and present two case studies: prostate segmentation, illustrating that for minimal anno…
That Label's Got Style: Handling Label Style Bias for Uncertain Image Segmentation
Kilian Zepf, Eike Petersen, Jes Frellsen +1
Segmentation uncertainty models predict a distribution over plausible segmentations for a given input, which they learn from the annotator variation in the training set. However, i…
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification
Kilian Zepf, Selma Wanna, Marco Miani +5
Image segmentation relies heavily on neural networks which are known to be overconfident, especially when making predictions on out-of-distribution (OOD) images. This is a common s…
Quantifying Topology In Pancreatic Tubular Networks From Live Imaging 3D Microscopy
Kasra Arnavaz, Oswin Krause, Kilian Zepf +5
Motivated by the challenging segmentation task of pancreatic tubular networks, this paper tackles two commonly encountered problems in biomedical imaging: Topological consistency o…