Automatic segmentation of intravascular ultrasound images: a texture-based approach

Abstract

Extraction of blood vessel boundaries from intravascular ultrasound images is essential in the quantitative analysis of cardiovascular functions. In this study, we are presenting a completely automated procedure for determining blood vessel borders. This approach uses textural operators to separate different tissue regions and morphological processing to refine extracted contours. The method was tested in a set of 29 intravascular ultrasound images obtained in vivo. To assess the performance of the method, we have compared the automatically processed images with the manual tracings, using three different criteria: correlation coefficient, match ratio, and relative error of computed shape parameters. In both contour detection and shape parameters estimation, the proposed method yielded consistently good results. Due to its robustness and accuracy, this approach is appropriate for clinical use, whereas computational efficiency of the method facilitates low-cost implementation.