Diffusion-Based Detection of Carotid Artery Lumen from Ultrasound Images
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Segmentation of the carotid intima-media region in B-mode ultrasound images
Image and Vision Computing
Segmentation of ultrasound images of the carotid using RANSAC and cubic splines
Computer Methods and Programs in Biomedicine
Carotid artery ultrasound image segmentation using fuzzy region growing
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Segmentation of ultrasonic images of the carotid
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Detection of arterial lumen in sonographic images based on active contours and diffusion filters
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
Fuzzy C-means clustering for segmenting carotid artery ultrasound images
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Expert Systems with Applications: An International Journal
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This study presents a novel automatic system for detecting the intimal and adventitial layers of the far common carotid artery (CCA) by applying the snake techniques. Cohen's snake is also modified and some criteria are added for our applications. In addition, the oscillating problem of using snakes is solved by properly choosing the time step from analysis of the frequency response of the filters. The snake scheme combined with a time diminishing gravity window and an external force makes it possible to detect the intima-media complex of the far CCA. Besides, a cost function assists the snake in selecting the optimal shape of adventitia layer. This mechanism is also helpful when there are plaques on the CCA wall. Moreover, this study compares the proposed snake and zip-lock snake with respect to the manual extraction contour. According to that comparison, the system can automatically detect the intimal and adventitial layers. In addition to that it does not need any manual correction and it is noise-resistant, the proposed system allows a user to quantitatively measure an important predictor of heart infarction and strokes.