Adventitia segmentation in intravascular ultrasound images based on improved Snake algorithm

作     者：Wang, Yousheng Gao, Xue Wang, Yuting Sun, Jinge 

作者机构：Beijing Univ Technol Beijing 100124 Peoples R China 

出 版 物：《OPTIK》 (光学)

年 卷 期：2021年第241卷

页      面：167175-167175页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

主　　题：Intravascular ultrasound images Segmentation Snake algorithm Structure tensor 

摘      要：Segmentation of coronary artery intravascular ultrasound (IVUS) images is the first step in assessing blood vessel morphology and detecting possible atherosclerotic lesions. To overcome the disadvantage of manual acquisition of initial contour in traditional Snake algorithm and construction of external force only from gradient information, an improved Snake algorithm is proposed for automatic outer membrane segmentation in intravascular ultrasound images. Firstly, we design a basic segmentation algorithm to automatically extract the approximate contour of the first frame, and this is iterated as the initial contour of the Snake algorithm. Next, the extended structure tensor is combined with the Snake algorithm to make it part of the external force of the Snake algorithm, and then the curve is evolved to complete the segmentation. To verify the effectiveness of the proposed method, this paper not only shows the experimental results qualitatively, but also quantitatively measures the RMSE and RDD indices. Comparative experiments show that the proposed method not only has higher accuracy, but also has better timeliness.