English

A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representation

Computer Vision and Pattern Recognition 2026-04-10 v4 Computational Geometry

Abstract

We introduce a novel approach for the reconstruction of tubular shapes from skeletal representations. Our method processes all skeletal points as a whole, eliminating the need for splitting input structure into multiple segments. We represent the tubular shape as a truncated signed distance function (TSDF) in a voxel hashing manner, in which the signed distance between a voxel center and the object is computed through a simple geometric algorithm. Our method does not involve any surface sampling scheme or solving large matrix equations, and therefore is a faster and more elegant solution for tubular shape reconstruction compared to other approaches. Experiments demonstrate the efficiency and effectiveness of the proposed method. Code is avaliable at https://github.com/wlsdzyzl/Dragon.

Keywords

Cite

@article{arxiv.2402.12797,
  title  = {A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representation},
  author = {Guoqing Zhang and Yang Li},
  journal= {arXiv preprint arXiv:2402.12797},
  year   = {2026}
}

Comments

9 pages (without reference), 6 figures

R2 v1 2026-06-28T14:54:11.175Z