Key result
A novel painting segmentation algorithm for B-mode ultrasound images allows for user-defined thresholding to accurately detect carotid artery lumen areas and identify plaque-thickened regions.
A novel painting segmentation algorithm improves lumen area detection and plaque identification in carotid artery B-mode ultrasound images.
May aid carotid plaque research imaging; clinical validation needed before practice adoption.
This paper presents a new blood flow detection scheme, where a novel painting segmentation algorithm is utilized in order to achieve the accurate area of lumens, within carotid artery B-mode ultrasound images. The scheme allows for user-defined thresholding providing tolerance levels within the contour detection process in order to overcome crippling interference noise and degrading artifacts in ultrasound images. Since plaque buildup obstructs the flow of blood in the carotid artery, this scheme can identify these severe plaque-thickened inflamed regions, through detecting high and low levels of blood flow.
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Hamou et al. (2005) studied Carotid artery plaque. Blood flow detection scheme using painting segmentation algorithm was evaluated on Accurate area of lumens and detection of blood flow levels. A novel painting segmentation algorithm for B-mode ultrasound images allows for user-defined thresholding to accurately detect carotid artery lumen areas and identify plaque-thickened regions.
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