A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information

We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then c...

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Main Authors: Huiyan Jiang, Baochun He, Di Fang, Zhiyuan Ma, Benqiang Yang, Libo Zhang
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Computational and Mathematical Methods in Medicine
Online Access:http://dx.doi.org/10.1155/2013/743870
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spelling doaj-bb4a67ffaeb9473eb862e0ef465550722020-11-24T20:41:19ZengHindawi LimitedComputational and Mathematical Methods in Medicine1748-670X1748-67182013-01-01201310.1155/2013/743870743870A Region Growing Vessel Segmentation Algorithm Based on Spectrum InformationHuiyan Jiang0Baochun He1Di Fang2Zhiyuan Ma3Benqiang Yang4Libo Zhang5Software College, Northeastern University, Shenyang, Liaoning 110819, ChinaSoftware College, Northeastern University, Shenyang, Liaoning 110819, ChinaSoftware College, Northeastern University, Shenyang, Liaoning 110819, ChinaSoftware College, Northeastern University, Shenyang, Liaoning 110819, ChinaRadiology Department, PLA General Hospital, Shenyang, Liaoning 110819, ChinaRadiology Department, PLA General Hospital, Shenyang, Liaoning 110819, ChinaWe propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure’s center points as the seed points of region growing segmentation. At last, the improved region growing method with branch-based growth strategy is used to segment the vessels. To prove the effectiveness of our algorithm, we use the retinal and abdomen liver vascular CT images to do experiments. The results show that the proposed vessel segmentation algorithm can not only extract the high quality target vessel region, but also can effectively reduce the manual intervention.http://dx.doi.org/10.1155/2013/743870
collection DOAJ
language English
format Article
sources DOAJ
author Huiyan Jiang
Baochun He
Di Fang
Zhiyuan Ma
Benqiang Yang
Libo Zhang
spellingShingle Huiyan Jiang
Baochun He
Di Fang
Zhiyuan Ma
Benqiang Yang
Libo Zhang
A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
Computational and Mathematical Methods in Medicine
author_facet Huiyan Jiang
Baochun He
Di Fang
Zhiyuan Ma
Benqiang Yang
Libo Zhang
author_sort Huiyan Jiang
title A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
title_short A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
title_full A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
title_fullStr A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
title_full_unstemmed A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
title_sort region growing vessel segmentation algorithm based on spectrum information
publisher Hindawi Limited
series Computational and Mathematical Methods in Medicine
issn 1748-670X
1748-6718
publishDate 2013-01-01
description We propose a region growing vessel segmentation algorithm based on spectrum information. First, the algorithm does Fourier transform on the region of interest containing vascular structures to obtain its spectrum information, according to which its primary feature direction will be extracted. Then combined edge information with primary feature direction computes the vascular structure’s center points as the seed points of region growing segmentation. At last, the improved region growing method with branch-based growth strategy is used to segment the vessels. To prove the effectiveness of our algorithm, we use the retinal and abdomen liver vascular CT images to do experiments. The results show that the proposed vessel segmentation algorithm can not only extract the high quality target vessel region, but also can effectively reduce the manual intervention.
url http://dx.doi.org/10.1155/2013/743870
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