title: Segmenting echocardiography images using B-Spline snake and active ellipse model.
abstract: In this paper, a fully automated method for segmenting Left Ventricle (LV) in echocardiography images is proposed. A new method named active ellipse model is developed to automatically find the best ellipse inside the LV chamber without intervention of any specialist. A modified B-Spline Snake algorithm is used to segment the LV chamber in which the initial contour is formed by the predefined ellipse. As a result of using active ellipse model, the segmentation is extricated from dealing with gaps within myocardium boundary which are highly problematic in echocardiography image segmentation. Based on the results obtained from different studies, the proposed method is faster and more accurate than previous approaches. Our method is evaluated on 20 sets of echocardiography images of patients; and acquired results (92.30 ± 4.45% dice's coefficient) indicate the proposed method has remarkable performance.
authors.affiliation: Research Center for Science and Technology in Medicine, RCSTIM, Tehran, Iran.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Marsousi
authors.forename: Javad
authors.initials: J
authors.lastname: Alirezaie
authors.forename: Alireza
authors.initials: A
authors.lastname: Ahmadian
authors.forename: Armen
authors.initials: A
authors.lastname: Kocharian
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004452:Echocardiography / Q000379:methods*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging*