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Detection and localization of coronary artery stenotic segments using image processing

机译:使用图像处理检测和定位冠状动脉狭窄段

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Coronary Artery Disease (CAD) is one of the emerging causes of death all over the world. Coronary angiography techniques for the detection of CAD lead to various complications like artery-dissection, arrhythmia and even death. In this paper we propose an image processing method for detecting and localizing the stenosis regions in the artery. The method is applied on the Digital Imaging and Communications in Medicine (DICOM)) image of the heart for the detection of stenosis. The region of interest is considered as the coronary arteries and is segmented using vessel enhancement diffusion filter along with dilation and erosion morphology. Centerlines of the segmented arteries are extracted using a fast marching based method. Detection of the stenosis is done by estimating the vessel diameter at each centerline location. The abrupt reduction in the diameter of the arteries is a sign of stenosis. The proposed method is evaluated with a set of images and it gives 86.67% accuracy for detecting the stenosis. This result validates the performance of the proposed method.
机译:冠状动脉疾病(CAD)是全世界新兴的死亡原因之一。用于检测CAD的冠状动脉造影技术会导致各种并发症,例如动脉解剖,心律不齐甚至死亡。在本文中,我们提出了一种用于检测和定位动脉狭窄区域的图像处理方法。该方法应用于心脏的数字成像和医学通信(DICOM)图像上以检测狭窄。感兴趣的区域被认为是冠状动脉,并使用血管增强扩散滤器以及扩张和糜烂形态进行了分割。使用基于快速行进的方法提取分段动脉的中心线。通过估计每个中心线位置处的血管直径来完成狭窄的检测。动脉直径的突然减小是狭窄的迹象。所提出的方法是通过一组图像进行评估的,它为狭窄检测提供了86.67%的准确性。该结果验证了所提出方法的性能。

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