16 citations · 25 across the 9 of their papers we have counts for
4 papers · 1 filter
Mask of truth: model sensitivity to unexpected regions of medical images
Théo Sourget, Michelle Hestbek-Møller, Amelia Jiménez-Sánchez +2
The development of larger models for medical image analysis has led to increased performance. However, it also affected our ability to explain and validate model decisions. Models…
Detection Transformer for Teeth Detection, Segmentation, and Numbering in Oral Rare Diseases: Focus on Data Augmentation and Inpainting Techniques
Hocine Kadi, Théo Sourget, Marzena Kawczynski +3
In this work, we focused on deep learning image processing in the context of oral rare diseases, which pose challenges due to limited data availability. A crucial step involves tee…
Copycats: the many lives of a publicly available medical imaging dataset
Amelia Jiménez-Sánchez, Natalia-Rozalia Avlona, Dovile Juodelyte +5
Medical Imaging (MI) datasets are fundamental to artificial intelligence in healthcare. The accuracy, robustness, and fairness of diagnostic algorithms depend on the data (and its…
[Citation needed] Data usage and citation practices in medical imaging conferences
Théo Sourget, Ahmet Akkoç, Stinna Winther +5
Medical imaging papers often focus on methodology, but the quality of the algorithms and the validity of the conclusions are highly dependent on the datasets used. As creating data…