Dehkordi Maryam Taghizadeh
Department of Engineering, Shahrekord University, Shahrekord 115, Iran.
J Med Signals Sens. 2016 Jul-Sep;6(3):150-7.
X-ray coronary angiography has been a gold standard in the clinical diagnosis and interventional treatment of coronary arterial diseases for decades. In angiography, a sequence of images is obtained, a few of which are suitable for physician inspection. This paper proposes an automatic algorithm for the extraction of one or more frames from an angiogram sequence, which is most suitable for diagnosis and analysis by experts or processors. The algorithm consists of two stages: In the first stage, the background and illumination in the angiogram sequence are omitted. By analyzing the histogram of the sequence, a feature is attributed to each frame. These features, determining the visibility of the vessel tree, are clustered by a fuzzy c-means method. In the second stage, the cardiac phase for each frame is specified. Using the results of both stages, the best frames in an angiogram sequence are obtained. To evaluate the proposed method, it has been tested on angiogram sequences from several patients. The results demonstrate the accuracy of the method. The performance and speed of our method indicate its usefulness in clinical applications.
几十年来，X射线冠状动脉造影一直是冠状动脉疾病临床诊断和介入治疗的金标准。在血管造影中，会获取一系列图像，其中只有少数几张适合医生检查。本文提出了一种自动算法，用于从血管造影序列中提取一帧或多帧图像，这些图像最适合专家或处理程序进行诊断和分析。该算法包括两个阶段：在第一阶段，去除血管造影序列中的背景和光照。通过分析序列的直方图，为每一帧赋予一个特征。这些决定血管树可见性的特征通过模糊c均值方法进行聚类。在第二阶段，确定每一帧的心动周期。利用两个阶段的结果，获得血管造影序列中的最佳帧。为了评估所提出的方法，对来自几位患者的血管造影序列进行了测试。结果证明了该方法的准确性。我们方法的性能和速度表明其在临床应用中的实用性。
