4 citations · 6 across the 4 of their papers we have counts for
5 papers
Multi-Dataset Diagnostic Utility of Clinical Visual Concepts in AI Systems for Dermatology
Linda Wermelinger, Simone Lionetti, Fabian Gröger +6
The clinical integration of AI systems in digital dermatology relies heavily on human trust. Clinically interpretable visual concepts can act as intermediate representations enhanc…
Picking the Right Image to Classify: Reliable-Input Selection in Teledermatology
Fabian Gröger, Marco Weishaupt, Philippe Gottfrois +6
Dermatology models face distribution shifts in teledermatology settings, where submitted images differ from the training data in lighting, angle, distance, focus, and framing. Thes…
Towards Reliable Dermatology Evaluation Benchmarks
Fabian Gröger, Simone Lionetti, Philippe Gottfrois +6
Benchmark datasets for digital dermatology unwittingly contain inaccuracies that reduce trust in model performance estimates. We propose a resource-efficient data-cleaning protocol…
Robust T-Loss for Medical Image Segmentation
Alvaro Gonzalez-Jimenez, Simone Lionetti, Philippe Gottfrois +3
This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution…
Intrinsic Self-Supervision for Data Quality Audits
Fabian Gröger, Simone Lionetti, Philippe Gottfrois +6
Benchmark datasets in computer vision often contain off-topic images, near duplicates, and label errors, leading to inaccurate estimates of model performance. In this paper, we rev…