Title
Segmentation of ultrasound images of the carotid using RANSAC and cubic splines.
Abstract
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.
Year
DOI
Venue
2011
10.1016/j.cmpb.2010.04.015
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
manual segmentation,geometric model,cubic spline,carotid boundary,far-end boundary,common carotid artery,different class,lumen boundary,ultrasound image,common carotid,different subject,far-end adventitia boundary,ransac,image segmentation,splines,smoothing spline,random sampling
Spline (mathematics),Computer vision,RANSAC,Computer science,Segmentation,Geometric modeling,Image processing,Image segmentation,Sampling (statistics),Artificial intelligence,Common carotid artery
Journal
Volume
Issue
ISSN
101
1
1872-7565
Citations 
PageRank 
References 
22
1.01
21
Authors
5
Name
Order
Citations
PageRank
Rui P. Rocha140735.91
Aurélio J. C. Campilho232140.49
Jorge Silva3704.39
Elsa Azevedo4895.88
Rosa Santos5532.50