2 citations · 3 across the 4 of their papers we have counts for
4 papers
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
Jun Ma, Feifei Li, Sumin Kim +79
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive co…
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:…
AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients
Rikhil Seshadri, Jayant Siva, Angelica Bartholomew +20
Kidney cancer is a global health concern, and accurate assessment of patient frailty is crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel…
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…