Mind the Gap: Mesh-Guided Repair of Broken Vessels

arXiv:2609.29779 · cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• nnU-Net — 21× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 3 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Meta-learning — 2× in this paper · explained in 2 episodes
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• A survey on shape-constraint deep learning for medical image segmentation
• Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge
• MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
• Efficient automatic segmentation for multi-level pulmonary arteries: The PARSE challenge
• On First-Order Meta-Learning Algorithms
• The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

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