Full Text:   <2129>

Summary:  <1421>

CLC number: TP391.4

On-line Access: 2019-08-29

Received: 2018-03-02

Revision Accepted: 2018-07-31

Crosschecked: 2019-08-15

Cited: 0

Clicked: 5699

Citations:  Bibtex RefMan EndNote GB/T7714


Shi-feng Zhao


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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.8 P.1099-1108


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

Author(s):  Yun Tian, Zi-feng Liu, Shi-feng Zhao

Affiliation(s):  College of Information Science and Technology, Beijing Normal University, Beijing 100875, China; more

Corresponding email(s):   zhao_shifeng@bnu.edu.cn

Key Words:  Vesselness filter, Neighborhood, Blood-vessel segmentation, Outlier

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.

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%T Vascular segmentation of neuroimages based on a prior shape and local statistics
%A Yun Tian
%A Zi-feng Liu
%A Shi-feng Zhao
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T1 - Vascular segmentation of neuroimages based on a prior shape and local statistics
A1 - Yun Tian
A1 - Zi-feng Liu
A1 - Shi-feng Zhao
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 20
IS - 8
SP - 1099
EP - 1108
%@ 2095-9184
Y1 - 2019
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1800129

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 magnetic- resonance-angiography images demonstrate that the proposed method can remove outliers while preserving the connectivity of vessel branches.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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