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脑卒中的发病与颈动脉易损斑块密切相关,早期识别颈动脉血管形态和分析颈动脉粥样斑块成分对于评估脑卒中发生风险具有重要意义。磁共振图像是诊断颈动脉疾病的有力工具,而颈动脉血管中心线提取是观察血管形态和定量分析斑块成分的基础。本文针对磁共振黑血图像的特点,在管状结构滤波预处理和阈值分割结果的基础上,采用一种树枝搜索算法提取血管中心线,并在7套磁共振黑血图像上进行了测试,结果表明,算法对于颈动脉血管大部分区域能够有效提取中心线。
The incidence of stroke is closely related to vulnerable plaque of carotid artery. Early identification of carotid artery morphology and analysis of carotid plaque components are of great significance for assessing the risk of stroke. Magnetic resonance imaging is a powerful tool for the diagnosis of carotid artery disease, and carotid artery centerline extraction is the basis for the observation of vascular morphology and quantitative analysis of plaque components. In this paper, based on the characteristics of magnetic resonance black blood images, based on the results of filtering and preprocessing of the tubular structure and the threshold segmentation results, a branch search algorithm was used to extract the centerlines of the blood vessels and tested on 7 sets of magnetic resonance black blood images. The results It shows that the algorithm can effectively extract the centerline for most of the carotid artery.