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Automatic detection of plaques with severe stenosis in coronary Vessels of CT Angiography

机译:自动检测CT血管造影冠状血管中严重狭窄的斑块

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Coronary artery disease is the end result of the accumulation of atheromatous plaques within the walls of coronary arteries and is the leading cause of death worldwide. Computed tomography angiography (CTA) has been proved to be very useful for accurate noninvasive diagnosis and quantification of plaques. However, the existing methods to measure the stenosis in the plaques are not accurate enough in mid and distal segments where the vessels become narrower. To alleviate this, we propose a method that consists of three stages namely, automatic extraction of coronary vessels; vessels straightening; lumen extraction and stenosis evaluation.In the first stage, the coronary vessels are segmented using a parametric approach based on circular vessel model at each point on the centerline. It is assumed that centerline information is available in advance. Vessel straightening in the second stage performs multi-planar reformat (MPR) to straighten the curved vessels. MPR view of a vessel helps to visualize and measure the plaques better. On the straightened vessel, lumen and vessel wall are segregated using a nearest neighbor classification. To detect the plaques with severe stenosis in the vessel lumen, we propose a "Diameter Luminal Stenosis" method for analyzing the smaller segments of the vessel. Proposed measurement technique identifies the segments that have plaques and reports the top three severely stenosed segments. Proposed algorithm is applied on 24 coronary vessels belonging to multiple cases acquired from Sensation 64 - slice CT and initial results are promising.
机译:冠状动脉疾病是冠状动脉壁内动脉粥样斑块积聚的最终结果,并且是全世界范围内死亡的主要原因。计算机断层造影血管造影(CTA)已被证明对于准确的非侵入性诊断和斑块定量非常有用。但是,现有的测量斑块狭窄的方法在血管变窄的中段和远端段不够准确。为了减轻这种情况,我们提出了一种方法,该方法包括三个阶段,即自动提取冠状血管;以及血管矫直;内腔提取和狭窄评估。 在第一阶段中,基于参数的方法基于圆形血管模型在中心线上的每个点对冠状动脉进行分割。假定中心线信息是预先可用的。第二阶段的容器拉直会执行多平面重新格式化(MPR),以拉直弯曲的血管。血管的MPR视图有助于更好地可视化和测量斑块。在拉直的血管上,管腔和血管壁使用最近的邻居分类法进行隔离。为了检测血管腔内严重狭窄的斑块,我们提出了一种“直径管腔狭窄”的方法来分析较小的血管段。建议的测量技术可识别出有斑块的段,并报告前三个严重狭窄的段。拟议的算法应用于从Sensation 64层CT获得的多个病例的24个冠状动脉血管中,初步结果是有希望的。

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