5 papers
nnFoundation: 3D Foundation Models for Radiology
Constantin Ulrich Harsy, Tassilo Wald, Karol Gotkowski +80
Radiological artificial intelligence has advanced rapidly, yet most systems remain narrowly task-specific, data-intensive, and fragile under domain shift. Foundation models promise…
TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation
Tristan Kirscher, Alexandra Ertl, Klaus Maier-Hein +3
Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous: inter-rater disagreement among experts reflects genuine uncertainty rather tha…
The MAMA-MIA Challenge: Advancing Generalizability and Fairness in Breast MRI Tumor Segmentation and Treatment Response Prediction
Lidia Garrucho, Smriti Joshi, Kaisar Kushibar +43
Breast cancer is the most frequently diagnosed malignancy among women worldwide and a leading cause of cancer-related mortality. Dynamic contrast-enhanced magnetic resonance imagin…
Deep Learning for Retinal Degeneration Assessment: A Comprehensive Analysis of the MARIO Challenge
Rachid Zeghlache, Ikram Brahim, Pierre-Henri Conze +47
The MARIO challenge, held at MICCAI 2024, focused on advancing the automated detection and monitoring of age-related macular degeneration (AMD) through the analysis of optical cohe…
nnLandmark: A Self-Configuring Method for 3D Medical Landmark Detection
Alexandra Ertl, Stefan Denner, Robin Peretzke +8
Landmark detection is central to many medical applications, such as identifying critical structures for treatment planning or defining control points for biometric measurements. Ho…