Segmentation in ultrasonic B-mode images of healthy carotid arteries using mixtures of Nakagami distributions and stochastic optimization.
The goal of this work is to perform a segmentation of the intimamedia thickness (IMT) of carotid arteries in view of computing various dynamical properties of that tissue, such as the elasticity distribution (elastogram). The echogenicity of a region of interest comprising the intima-media layers, the lumen, and the adventitia in an ultrasonic B-mode image is modeled by a mixture of three Nakagami distributions. In a first step, we compute the maximum a posteriori estimator of the proposed model, using the expectation maximization (EM) algorithm. We then compute the optimal segmentation based on the estimated distributions as well as a statistical prior for disease-free IMT using a variant of the exploration/selection (ES) algorithm. Convergence of the ES algorithm to the optimal solution is assured asymptotically and is independent of the initial solution. In particular, our method is well suited to a semi-automatic context that requires minimal manual initialization. Tests of the proposed method on 30 sequences of ultrasonic B-mode images of presumably disease-free control subjects are reported. They suggest that the semi-automatic segmentations obtained by the proposed method are within the variability of the manual segmentations of two experts.
Destrempes
François
F
Laboratoire de Biorhéologie et d'Ultrasonographie Médicale (LBUM), Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, QC, H2L 2W5 Canada.
Meunier
Jean
J
Giroux
Marie-France
MF
Soulez
Gilles
G
Cloutier
Guy
G
D000465:Algorithms; D001499:Bayes Theorem; D002339:Carotid Arteries / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D013269:Stochastic Processes; D014463:Ultrasonography / Q000379:methods