Paper Info
Title
Segmentation of plaques in sequences of ultrasonic B-mode images of carotid arteries based on motion estimation and a Bayesian model.
Abstract
The goal of this work is to perform a segmentation of atherosclerotic plaques in view of evaluating their burden and to provide boundaries for computing properties such as the plaque deformation and elasticity distribution (elastogram and modulogram). The echogenicity of a region of interest comprising the plaque, the vessel lumen, and the adventitia of the artery wall in an ultrasonic B-mode image was modeled by mixtures of three Nakagami distributions, which yielded the likelihood of a Bayesian segmentation model. The main contribution of this paper is the estimation of the motion field and its integration into the prior of the Bayesian model that included a local geometrical smoothness constraint, as well as an original spatiotemporal cohesion constraint. The Maximum A Posteriori (MAP) of the proposed model was computed with a variant of the Exploration/Selection (ES) algorithm. The starting point is a manual segmentation of the first frame. The proposed method was quantitatively compared with manual segmentations of all frames by an expert technician. Various measures were used for this evaluation, including the mean point-to-point distance and the Hausdorff distance. Results were evaluated on 94 sequences of 33 patients (for a total of 8988 images). We report a mean point-to- point distance of 0.24 ± 0.08 mm and a Hausdorff distance of 1.24 ± 0.40 mm. Our tests showed that the algorithm was not sensitive to the degree of stenosis or calcification.
Year
DOI
Venue
2011
10.1109/TBME.2011.2127476
IEEE Trans. Biomed. Engineering
Keywords
Field
DocType
Bayes methods,biomechanics,biomedical ultrasonics,blood vessels,deformation,diseases,elasticity,image segmentation,image sequences,medical image processing,motion estimation,Bayesian segmentation model,Hausdorff distance,Nakagami distributions,adventitia,artery wall,atherosclerotic plaques,calcification,carotid arteries,echogenicity,elasticity distribution,elastogram,expert technician,exploration-selection algorithm,local geometrical smoothness constraint,maximum A posteriori,modulogram,motion estimation,motion field,plaque deformation,spatiotemporal cohesion constraint,stenosis,ultrasonic B-mode image,vessel lumen,B-Mode,Bayesian model,carotid artery,expectation maximization algorithm,exploration selection algorithm,mixtures of Nakagami distributions,motion estimation,plaque,segmentation,stochastic optimization,tracking,ultrasound
Computer vision,Motion field,Computer science,Segmentation,Expectation–maximization algorithm,Image segmentation,Hausdorff distance,Artificial intelligence,Maximum a posteriori estimation,Region of interest,Motion estimation
Journal
Volume
Issue
ISSN
58
8
1558-2531
Citations 
PageRank 
References 
12
0.74
14
Authors
5
Name
Order
Citations
PageRank
François Destrempes1948.36
Jean Meunier267359.36
Marie-France Giroux3532.68
Gilles Soulez415718.24
Guy Cloutier5685.47