activity
20222025
most citedLabeling instructions matter in biomedical image analysis

3 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

physics.med-ph2025

Anthropomorphic tissue-mimicking phantoms for oximetry validation in multispectral optical imaging

Kris Kristoffer Dreher, Janek Groehl, Friso Grace +11

Significance: Optical imaging of blood oxygenation (sO) can be achieved based on the differential absorption spectra of oxy- and deoxy-haemoglobin. A key challenge in realising…

cs.CV20242 cited

Quality Assured: Rethinking Annotation Strategies in Imaging AI

Tim Rädsch, Annika Reinke, Vivienn Weru +5

This paper does not describe a novel method. Instead, it studies an essential foundation for reliable benchmarking and ultimately real-world application of AI-based image analysis:…

cs.CV20231 cited

Why is the winner the best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru +122

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…

cs.CV20231 cited

Self-distillation for surgical action recognition

Amine Yamlahi, Thuy Nuong Tran, Patrick Godau +9

Surgical scene understanding is a key prerequisite for contextaware decision support in the operating room. While deep learning-based approaches have already reached or even surpas…

cs.CV20223 cited

Labeling instructions matter in biomedical image analysis

Tim Rädsch, Annika Reinke, Vivienn Weru +7

Biomedical image analysis algorithm validation depends on high-quality annotation of reference datasets, for which labeling instructions are key. Despite their importance, their op…