• Home
  • Journals
  • Focus
  • Conference
  • Sign in

Outline

  • Abstract
  • Keywords

Figures(5)

标签(1)

Table 1

其他(2)

PDF
Document

Frontiers of Information Technology & Electronic Engineering

2019, Volume 20,  Issue 8, Pages 1099-1108
    • PDF
    • collect
    • share

    Vascular segmentation of neuroimages based on a prior shape and local statistics

    1. College of Information Science and Technology, Beijing Normal University, Beijing 100875, China
    2. Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing 100875, China

    Show More
    10.1631/FITEE.1800129
    Cite this article
    Yun TIAN, Zi-feng LIU, Shi-feng ZHAO.Vascular segmentation of neuroimages based on a prior shape and local statistics[J].Frontiers of Information Technology & Electronic Engineering,2019,20(8):1099-1108.

    Abstract

    Abstract Fast and accurate extraction of vascular structures from medical images is fundamental for many clinical procedures. However, most of the vessel segmentation techniques ignore the existence of the isolated and redundant points in the segmentation results. In this study, we propose a vascular segmentation method based on a prior shape and local statistics. It could efficiently eliminate outliers and accurately segment thick and thin vessels. First, an improved vesselness filter is defined. This quantifies the likelihood of each voxel belonging to a bright tubular-shaped structure. A matching and connection process is then performed to obtain a blood-vessel mask. Finally, the region-growing method based on local statistics is implemented on the vessel mask to obtain the whole vascular tree without outliers. Experiments and comparisons with Frangi’s and Yang’s models on real magneticresonance-angiography images demonstrate that the proposed method can remove outliers while preserving the connectivity of vessel branches.

    Keywords

    Vesselness filter ; Neighborhood ; Blood-vessel segmentation ; Outlier
    Previous article in issue
    article in issue Next
    登录后,您可以进行评论。请先登录

    评论

    评论

    • 所有评论
     咋就跳到顶部了
    2019-04-23 11:24:14
    回复 (0)
    inspur  手机账号
    2019-05-10 11:30:17
    回复 (0)

    Read

    6

    Download

    0

    Related Research

    Current Issue

    • Copyright © 2015 Engineering Sciences Press, China
    • Beijing ICP 11030251-2

    Wechat

    Weibo