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A Region Growing Vessel Segmentation Algorithm Based on Spectrum Information
Author(s) -
Huiyan Jiang,
Baochun He,
Fang Di,
Zhiyuan Ma,
Benqiang Yang,
Libo Zhang
Publication year - 2013
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2013/743870
Subject(s) - segmentation , region growing , feature (linguistics) , computer science , artificial intelligence , algorithm , enhanced data rates for gsm evolution , pattern recognition (psychology) , image segmentation , computer vision , scale space segmentation , linguistics , philosophy
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.

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