Atherosclerotic carotid wall segmentation in ultrasound images using Markov random fields

This work explores the segmentation of the intima-media complex (IMC) of the common carotid artery (CCA) wall for the evaluation of the intima media thickness (IMT) on B-mode ultrasound images. The IMT provides important clinical information for the evaluation of the risk of developing atherosclerosis. The algorithm begins with speckle removal, which is followed by the use of a Hough transform for boundary detection and image normalization. The corresponding results provide the initial statistical information needed for a Markov random field (MRF) segmentation. The method lends itself to the development of a fully automatic method for the delineation of the IMC. The mean and standard deviation of the automatically segmented results are 0.7855 and 0.1738 mm and the corresponding value for the ground truth IMT are 0.7959 and 0.1875 mm. The Wilcoxon rank sum test shows no significant differences. Future work will investigate the proposed method using a larger number of tissue classes and on more subjects.