Automated detection of the carotid artery wall in B-mode ultrasound images using active contours initialized by the Hough Transform.
Automatic segmentation of the arterial lumen from ultrasound images is an important and often challenging task in clinical diagnosis. We previously used the Hough Transform (HT) to automatically extract circles from sequences of B-mode ultrasound images of transverse sections of the carotid artery. In this paper, an active-contour-based methodology is suggested, initialized by the HT circle, in an attempt to extend previous findings and to accurately detect the arterial wall boundary. The methodology is based on the generation of a gradient vector flow field, an approach attempting to overcome conventional active contours constraints. Contour estimation is then achieved by deforming the initial curve (circle) based on the gradient vector flow field. In ten normal subjects, the specificity and accuracy of the segmentation were on average higher than 0.98, whereas the sensitivity was higher than 0.82. The methodology was also applied to four subjects with atherosclerosis, in which sensitivity, specificity and accuracy were comparable to those of normal subjects. In conclusion, the HT-initialized active contours methodology provides a reliable tool to detect the carotid artery wall in ultrasound images and can be used in clinical practice.
Stoitsis
J
J
Department of Electrical and Computer Engineering, National Technical University of Athens, Greece.
Golemati
S
S
Kendros
S
S
Nikita
K S
KS
D000328:Adult; D000465:Algorithms; D050197:Atherosclerosis / Q000000981:diagnostic imaging / Q000473:pathology*; D001331:Automation; D002339:Carotid Arteries / Q000000981:diagnostic imaging* / Q000473:pathology; D001330:Electronic Data Processing; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014465:Ultrasonics; D014463:Ultrasonography / Q000379:methods