8 citations · 9 across the 3 of their papers we have counts for
4 papers
Sparse cubical complexes for efficient topology-preservation in image data
Alexander H. Berger, Marco Fontana, Daniel Rueckert +3
Persistent homology (PH) is a frequently used tool for extracting and preserving topological information from image data, particularly in image segmentation, where preservation of…
Topograph: An efficient Graph-Based Framework for Strictly Topology Preserving Image Segmentation
Laurin Lux, Alexander H. Berger, Alexander Weers +4
Topological correctness plays a critical role in many image segmentation tasks, yet most networks are trained using pixel-wise loss functions, such as Dice, neglecting topological…
Efficient Betti Matching Enables Topology-Aware 3D Segmentation via Persistent Homology
Nico Stucki, Vincent Bürgin, Johannes C. Paetzold +1
In this work, we propose an efficient algorithm for the calculation of the Betti matching, which can be used as a loss function to train topology aware segmentation networks. Betti…
Topologically Faithful Multi-class Segmentation in Medical Images
Alexander H. Berger, Nico Stucki, Laurin Lux +6
Topological accuracy in medical image segmentation is a highly important property for downstream applications such as network analysis and flow modeling in vessels or cell counting…