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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Series: | Computational and Mathematical Methods in Medicine |
Online Access: | http://dx.doi.org/10.1155/2013/743870 |
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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 |
work_keys_str_mv |
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1716825565880647680 |