Title: Coronary Plaque Boundary Detection in Intravascular Ultrasound Image by Using Hybrid Modified Level Set Method and Fuzzy Inference

Year of Publication: Nov - 2013
Page Numbers: 68-74
Authors: Syaiful Anam, Eiji Uchino, Noriaki Suetake
Conference Name: The Second International Conference on Informatics Engineering & Information Science (ICIEIS2013)
- Malaysia


This paper describes a boundary detection of coronary plaque by a hybrid of a modified level set method and a fuzzy inference. The standard level set method to detect an image boundary commonly uses an image gradient for calculating a speed function. But the speed function of the level set cannot work well within an intravascular ultrasound (IVUS) image, which is the target of this paper. Therefore, we proposed a method for coronary boundary detection in IVUS image by using a modified level set method. In that method, the image gradient in the speed function is substituted by the weighted image separability. However, some regions of the IVUS image often becomes shadowed and then contains no texture information, due to the presence of the guide wire. Thus the modified level set method fails to detect the plaque boundary in those regions. To solve this problem, we further propose in this paper, a hybrid of the modified level set method and the T-S fuzzy model. The present method has been more successful in the accuracy of plaque boundary detection.