7 citations · 8 across the 3 of their papers we have counts for
3 papers
Mask-HybridGNet: Graph-based segmentation with emergent anatomical correspondence from pixel-level supervision
Nicolás Gaggion, Maria J. Ledesma-Carbayo, Stergios Christodoulidis +2
Graph-based medical image segmentation represents anatomical structures using boundary graphs, providing fixed-topology landmarks and inherent population-level correspondences. How…
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models
Nicolás Gaggion, Maria Vakalopoulou, Diego H. Milone +1
Learning anatomical segmentation from heterogeneous labels in multi-center datasets is a common situation encountered in clinical scenarios, where certain anatomical structures are…
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Alessa Hering, Lasse Hansen, Tony C. W. Mok +50
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medi…