CORONARY ARTERY DETECTION IN X-RAY ANGIOGRAM WITH FUZZY C-MEANS CLUSTERING ALGORITHM

Q4 Engineering
Leila Kiani
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引用次数: 0

Abstract

This paper presents an algorithm for the segmentation of Blood Vessels from x-ray angiography of coronary artery images using Matched filters and Otsu thresholding . Identifying these arteries is a difficult process because of the vessel overlapping, and superimposition with various anatomical structures such as the ribs, the spine and the heart chambers. Firstly, the 3D Fourier and 2D Wavelet transforms are first used to eliminate the background and reduce noise in the images. Afterwards, a set of matched filters was applied to enhance the coronary arteries in the images. Finally with Otsu thresholding and 8-connected neighborhood pixels the segmented vessel was obtained.
基于模糊c均值聚类算法的x线血管造影冠状动脉检测
本文提出了一种基于匹配滤波和Otsu阈值的冠状动脉x线造影图像血管分割算法。识别这些动脉是一个困难的过程,因为血管重叠,并与各种解剖结构,如肋骨,脊柱和心脏腔重叠。首先,利用三维傅里叶变换和二维小波变换去除图像中的背景和噪声;然后,使用一组匹配的滤波器对图像中的冠状动脉进行增强。最后利用Otsu阈值法和8连通的邻域像素得到分割后的血管。
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来源期刊
Majlesi Journal of Electrical Engineering
Majlesi Journal of Electrical Engineering Engineering-Electrical and Electronic Engineering
CiteScore
1.20
自引率
0.00%
发文量
9
期刊介绍: The scope of Majlesi Journal of Electrcial Engineering (MJEE) is ranging from mathematical foundation to practical engineering design in all areas of electrical engineering. The editorial board is international and original unpublished papers are welcome from throughout the world. The journal is devoted primarily to research papers, but very high quality survey and tutorial papers are also published. There is no publication charge for the authors.
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