A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel thinning with two-subiteration algorithms
Communications of the ACM
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
SIAM Journal on Scientific Computing
Engineering a freehand 3D ultrasound system
Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Towards recognition-based variational segmentation using shape priors and dynamic labeling
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
IEEE Transactions on Image Processing
Speckle reducing anisotropic diffusion
IEEE Transactions on Image Processing
Edge detection in ultrasound imagery using the instantaneous coefficient of variation
IEEE Transactions on Image Processing
Carotid artery image segmentation using modified spatial fuzzy c-means and ensemble clustering
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Computer Methods and Programs in Biomedicine
Expert Systems with Applications: An International Journal
Computer Methods and Programs in Biomedicine
A novel method for pulmonary embolism detection in CTA images
Computer Methods and Programs in Biomedicine
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A new algorithm is proposed for the semi-automatic segmentation of the near-end and the far-end adventitia boundary of the common carotid artery in ultrasound images. It uses the random sample consensus method to estimate the most significant cubic splines fitting the edge map of a longitudinal section. The consensus of the geometric model (a spline) is evaluated through a new gain function, which integrates the responses to different discriminating features of the carotid boundary: the proximity of the geometric model to any edge or to valley shaped edges; the consistency between the orientation of the normal to the geometric model and the intensity gradient; and the distance to a rough estimate of the lumen boundary. A set of 50 longitudinal B-mode images of the common carotid and their manual segmentations performed by two medical experts were used to assess the performance of the method. The image set was taken from 25 different subjects, most of them having plaques of different classes (class II to class IV), sizes and shapes. The quantitative evaluation showed promising results, having detection errors similar to the ones observed in manual segmentations for 95% of the far-end boundaries and 73% of the near-end boundaries.