Coronary plaque classification through intravascular ultrasound radiofrequency data analysis using self-organizing map
Coronary plaque classification through intravascular ultrasound radiofrequency data analysis using self-organizing map
复制标题
使用自组织图通过血管内超声射频数据分析进行冠状动脉斑块分类
DOI：
10.1109/ultsym.2005.1603283
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
M. Yoshizawa
中科院分区：
文献类型：
--
作者：
T. Iwamoto;A. Tanaka;Y. Saijo;M. Yoshizawa
血管内超声（IVUS）是评价冠状动脉粥样硬化斑块的重要临床工具。利用IVUS，我们可以获得冠状动脉横断面的高分辨率回波图像。然而，仅利用超声心动图很难对斑块进行准确分类。提出了一种基于自组织映射（SOM）的血管内超声射频信号分类方法。冠状动脉病变患者IVUS超声心动图的特征ROI（感兴趣区域）由专家医生选择，SOM从这些ROI中学习。SOM对纤维斑块、血液、钙化斑块和中膜区的分类准确率分别为95.9%、99.5%、96.2%和16.3%。这一结果表明，所提出的技术是有用的冠状动脉斑块的自动表征。
Intravascular ultrasound (IVUS) is an important clinical tool in the assessment of atherosclerotic plaque in coronary artery diseases. Using IVUS, we can obtain high resolution echo image of cross-sections of the coronary artery. However, it is difficult to accurately classify plaques by using the echogram only. We propose a method of IVUS Radiofrequency (RF) signal classification using self-organizing map (SOM). Characteristic ROIs (region of interest) of the IVUS echogram of patients with coronary lesions were selected by an expert medical doctor, and the SOM learned from these ROIs. The SOM could classify the RF signals with accuracies of 95.9% for fibrous plaque, 99.5% for blood, 96.2% for calcified plaque and 16.3% for media regions. This result suggests that the proposed technique is useful for automatic characterization of plaque in coronary artery.