187 citations · 721 across the 60 of their papers we have counts for
5 papers · 1 filter
Leveraging point annotations in segmentation learning with boundary loss
Eva Breznik, Hoel Kervadec, Filip Malmberg +4
This paper investigates the combination of intensity-based distance maps with boundary loss for point-supervised semantic segmentation. By design the boundary loss imposes a strong…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
Source Identification: A Self-Supervision Task for Dense Prediction
Shuai Chen, Subhradeep Kayal, Marleen de Bruijne
The paradigm of self-supervision focuses on representation learning from raw data without the need of labor-consuming annotations, which is the main bottleneck of current data-driv…
On the dice loss gradient and the ways to mimic it
Hoel Kervadec, Marleen de Bruijne
In the past few years, in the context of fully-supervised semantic segmentation, several losses -- such as cross-entropy and dice -- have emerged as de facto standards to supervise…
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…