A New Gradient-Based Algorithm for Edge Detection in Ultrasonic Carotid Artery Images

In human clinical studies, digital B-Mode ultrasound images of carotid and femoral artery walls are used to measure Intima-Media Thickness (IMT). IMT represents the arterial intima-media complex and is a validated surrogate parameter for atherosclerosis and cardiovascular disease risk. Conventionally, IMT is obtained by tracing the ultrasound interfaces of the arterial far walls manually. The manual tracing, however, may be replaced by an automated approach in order to decrease image analysis variability and improve consistency and efficiency of the imaging laboratory. In this paper, we present and test a novel automated edge detection method which employs a multi-step gradient based algorithm. The new method principally uses intensity, intensity gradient, and interface continuity of pixels to determine the ultrasound interfaces. In our investigations, we used the far wall of the common carotid artery to test the proposed algorithm. As our results show, the novel algorithm greatly eliminates subjectivity associated with conventional manual tracing and semi-automated gradient methods that employ seed point selection. The new method can therefore have a great potential in atherosclerosis studies and clinical trials.