1 citations · 2 across the 4 of their papers we have counts for
4 papers
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…