Paper
13 March 1996 Detecting interfaces on ultrasound images of the carotid artery by dynamic programming
Author Affiliations +
Proceedings Volume 2666, Image and Video Processing IV; (1996) https://doi.org/10.1117/12.234746
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
A dynamic programming edge following procedure is applied to ultrasound images of the carotid artery. The objective is to automatically determine the 'far wall' interfaces of the common carotid artery. The far wall interfaces are then used to estimate the far wall thickness, which is an important metric for disease diagnosis and treatment evaluation. A current system uses human readers to determine the carotid artery interfaces using digitized images on a computer display. This process is time consuming and difficult to control, since readers tend to vary over time in the way in which they identify interfaces. In addition, different readers tend to identify interfaces in slightly different ways. The edge following procedure is designed to apply a consistent and objective criteria to all images in order to reduce the variability in far wall thickness estimates. The edge following procedure works by joining local peaks in the image gradient. The gradient is estimated by a Sobel operator, and dynamic programming is used to join the peaks into a smooth edge. The dynamic programming is necessary to combat the effects of noise and speckle in the ultrasound images. The paper describes the dynamic programming cost function formulation and discuses the algorithm performance.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard J. Kozick "Detecting interfaces on ultrasound images of the carotid artery by dynamic programming", Proc. SPIE 2666, Image and Video Processing IV, (13 March 1996); https://doi.org/10.1117/12.234746
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CITATIONS
Cited by 12 scholarly publications.
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KEYWORDS
Arteries

Computer programming

Ultrasonography

Human-machine interfaces

Edge detection

Detection and tracking algorithms

Speckle

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