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A monocentric centerline extraction method for ring-like blood vessels.

Centerline is generally used to measure topological and morphological parameters of blood vessels, which is pivotal for the quantitative analysis of vascular diseases. However, previous centerline extraction methods have two drawbacks on complex blood vessels, represented as the failure on ring-like...

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Published in:Medical & Biological Engineering & Computing Vol. 56; no. 4; pp. 695 - 708
Main Authors: Zhao, Fengjun, Sun, Feifei, Hou, Yuqing, Chen, Yanrong, Chen, Dongmei, Cao, Xin, Yi, Huangjian, Wang, Bin, He, Xiaowei, Liang, Jimin
Format: Journal Article
Published: Springer Nature Apr2018
Online Access:View this record in EBSCOhost
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      jtl: Medical & Biological Engineering & Computing
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      dt: Apr2018
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-017-1717-8
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        atl: A monocentric centerline extraction method for ring-like blood vessels.
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        au:
          Zhao, Fengjun
          Sun, Feifei
          Hou, Yuqing
          Chen, Yanrong
          Chen, Dongmei
          Cao, Xin
          Yi, Huangjian
          Wang, Bin
          He, Xiaowei
          Liang, Jimin
        affil: School of Information Sciences and Technology, Northwest University, 710069, Xi’an, Shaanxi, China
      sug:
        subj:
          Magnetic Resonance Angiography Methods
          Image Processing, Computer Assisted Methods
          Blood Vessels
          Algorithms
          Resource Databases
      ab: Centerline is generally used to measure topological and morphological parameters of blood vessels, which is pivotal for the quantitative analysis of vascular diseases. However, previous centerline extraction methods have two drawbacks on complex blood vessels, represented as the failure on ring-like structures and the existing of multi-voxel width. In this paper, we propose a monocentric centerline extraction method for ring-like blood vessels, which consists of three components. First, multiple centerlines are generated from the seed points that are chosen by randomly sprinkling points on blood vessel data. Second, multi-centerline fusion is used to repair the notches of centerlines on ring-like vessels, and the local maximum of distance from oundary is employed to remedy the missing centerline points. Finally, monocentric processing is devised to keep the vascular centerline with single voxel width. We compared the proposed method with Wan et al.'s method and topological thinning on five groups of data including synthesized vascular datasets and MR brain images. The result showed the proposed method performed better than the two contrast methods both by visual inspection and by quantitative assessment, which demonstrated the performance of the proposed method on ring-like blood vessels as well as the elimination of multi-voxel width points.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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