关键词: 血管内超声图像, 图像分割, 图像配准, 仿射变换, 管腔内膜

Abstract: For the sequence intravascular ultrasound (IVUS) images, there are great similarities between two adjacent frames, and a new method based on sequential IVUS image registration for automatic extraction of lumen is proposed. Firstly, in order to realize the automation of extraction process, the morphological operation and the connected component method are used to extract the approximate lumen contour of the initial frame. Secondly, the target region, which includes both foreground and background pixels, is implicitly represented by a level set. The color histogram feature of target region foreground pixels and background pixels are modeled on two adjacent frames because of its merits such as independence of scaling and rotation, robustness to partial occlusions, low computational cost, etc. The Bhattacharyya coefficient measures the similarity between two adjacent frames. The higher the Bhattacharyya coefficient between target model and candidate target model is, the higher the similarity between them is. By establishing affine transformation model, the contour is more accurately located near the lumen. Finally, the segmentation procedure refines the affine transformation estimated in the registration stage, and computes the target’s true shape accurately. The target contour curve is accurately converged to the lumen of the IVUS image by the variational method and the steepest ascent method. Compared with the literature [17], the RMSE of this method is reduced by 0.124 on average, and the RDD is reduced by 0.51% on average. Compared with literature [4], the RMSE of this method is reduced by 0.063 on average, and the RDD is reduced on average by 0.16%. The experimental results show that the method can accurately extract the lumen of several consecutive frame IVUS images.

Key words:  intravascular ultrasound image (IVUS), image segmentation, image registration, affine transformation, lumen