Intravascular Ultrasound (IVUS) is a diagnostic imaging technique that provides tomographic visualization of coronary arteries. Important challenges in analysis of IVUS images are speckle noise, artifacts of catheter and calcified shadows. In this paper, we present a method for the automated detection of outer (media-adventitia) border of vessel by the use of geometric deformable models. Speckle noise is reduced with median filter. The initial contour is extracted using Canny edge detection and finally the calcified regions are characterized by using Bayes classifier and thresholding methods. The proposed methods were evaluated on 60 IVUS images from 7 different patients. The results show that the border detection method was statistically accurate and in the range of inter observer variability (based on the used validation methods). Bayesian classifier enables us to characterize the regions of interest, with a sensitivity and specificity of 92.67% and 98.5% respectively. © 2008 Springer-Verlag.
CITATION STYLE
Roodaki, A., Najafi, Z., Soltanzadi, A., Taki, A., Setarehdan, S. K., & Navab, N. (2008). Detection of outer layer of the vessel wall and characterization of calcified plaques in IVUS images. In Communications in Computer and Information Science (Vol. 6 CCIS, pp. 629–636). https://doi.org/10.1007/978-3-540-89985-3_77
Mendeley helps you to discover research relevant for your work.