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作 者:LI Xing-wen ZHOU Gang YANG Ting ZHANG Qi QIAO Hui-ting LI Shu-yu LI De-yu
机构地区:[1]School of Biological Science and Medical Engineering, Beihang University
出 处:《Chinese Journal of Biomedical Engineering(English Edition)》2018年第3期93-99,共7页中国生物医学工程学报(英文版)
摘 要:Cerebral artery stenosis is an important cause and risk factor to ischemic cerebrovascular disease. This paper describes a simple and effective method for the detection of cerebral artery stenosis in magnetic resonance angiography(MRA).Because of the complex structure of the brain blood vessels, the fast and accurate segmentation method is needed. Here, we used the information of the maximum intensity projection(MIP) image to get 3 D vascular structure. As skeleton was one of useful measures for charactering region-based shape features, we extracted 3 D-skeleton of blood vessels by using fast marching method(FMM). Finally, the accurate cross-sectional areas based on cerebrovascular skeleton were computed to determine the location and extent of vascular stenosis. The results showed that our method could effectively detect the cerebral artery stenosis.Cerebral artery stenosis is an important cause and risk factor to ischemic cerebrovascular disease. This paper describes a simple and effective method for the detection of cerebral artery stenosis in magnetic resonance angiography(MRA).Because of the complex structure of the brain blood vessels, the fast and accurate segmentation method is needed. Here, we used the information of the maximum intensity projection(MIP) image to get 3 D vascular structure. As skeleton was one of useful measures for charactering region-based shape features, we extracted 3 D-skeleton of blood vessels by using fast marching method(FMM). Finally, the accurate cross-sectional areas based on cerebrovascular skeleton were computed to determine the location and extent of vascular stenosis. The results showed that our method could effectively detect the cerebral artery stenosis.
关 键 词:cerebral ARTERY STENOSIS MR ANGIOGRAPHY 3D segmentation 3D-skeletonization CROSS-SECTIONAL profiles
分 类 号:R743[医药卫生—神经病学与精神病学]
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