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Vesselpose method reconstructs accurate vascular graphs from 3D images

Researchers have developed Vesselpose, a novel method for reconstructing accurate vascular graphs from 3D medical images. This approach predicts voxel-wise vessel direction vectors alongside segmentation masks, then uses a modified TEASAR algorithm to extract the graph. Vesselpose achieves state-of-the-art results on benchmark datasets and demonstrates improved topological accuracy, enabling better separation of closely apposed vessel segments and handling of multiple vascular trees. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Improves topological accuracy in vascular graph reconstruction for medical imaging applications.

RANK_REASON Academic paper published on arXiv detailing a new method for medical image analysis.

Read on arXiv cs.CV →

COVERAGE [2]

  1. arXiv cs.CV TIER_1 · Rajalakshmi Palaniappan, Christoph Karg, Nemesio Navarro-Arambula, Peter Hirsch, Kristin Kraeker, Lisa Mais, Dagmar Kainmueller ·

    Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images

    arXiv:2605.00538v1 Announce Type: new Abstract: Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment-then-fix paradigm is fundamentally limited regarding its suitability for modeli…

  2. arXiv cs.CV TIER_1 · Dagmar Kainmueller ·

    Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images

    Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment-then-fix paradigm is fundamentally limited regarding its suitability for modeling the task of complete and topologically accura…