基于主动轮廓模型的颈动脉内中膜厚度提取
首发时间:2013-03-19
摘要:动脉粥样硬化(Atherosclerosis)形成的不稳定斑块的破裂,血栓形成和血管阻塞被认为是急性心脑血管疾病(Cardiovascular Disease,CVD)发病的主要原因。研究表明,颈动脉的内中膜厚度可以作为心肌梗塞和中风的预测指标,它和动脉粥样硬化也有很大的相关性。本文提出了一种基于主动轮廓模型的自动膜提取法(Automated Layer Extraction based on Snake,ALES)提取超声颈动脉内中膜厚度,并将其与一种通过使用新的外部能量函数改进的活动模型方法进行对比从而对其进行验证。通过对两种方法的分割结果进行对比,实验结果表明,基于主动轮廓模型的自动膜提取方法在超声颈动脉内中膜厚度的提取中可得到更加准确的结果。
关键词: 生物医学工程 图像分割 基于主动轮廓模型的自动膜提取法 颈动脉内中膜厚度
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Carotid artery intima-media thickness extraction based on Snake
Abstract:Atherosclerosis plaque rupture due to its instable formation, thrombosis and vascular occlusion is considered to be the main cause of the incidence of acute cardiovascular disease Cardiovascular Disease (CVD). Studies have indicated carotid intima-media thickness as a predictor of myocardial infarction and stroke. It also has great relevance with atherosclerosis. We proposed an Automated Layer Extraction based on Snake to extract ultrasound carotid intima-media thickness and validated it by comparing it with an improved active model approach which used a new external energy function. By comparing the segmentation results of the two approaches, it is demonstrated that the Automated Layer Extraction based on Snake approach can obtain better results to extract ultrasound carotid intima-media thickness.
Keywords: Biomedical Engineering Image segmentation Automated Layer Extraction based on Snake Carotid intima-media thickness
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