A Geometric Algorithm for Blood Vessel Reconstruction from Skeletal Representation

Guoqing Zhang, Yang Li

Abstract: We introduce a novel approach for blood vessel reconstruction from skeletal representations. Our method processes all skeletal points as a whole, eliminating the need for splitting input structure into multiple segments. We represent such 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 vessel reconstruction compared to other approaches. Extensive experiments demonstrate the efficiency and effectiveness of the proposed method. Code is avaliable at https://github.com/wlsdzyzl/Dragon.