title: Automatic 3-D segmentation of endocardial border of the left ventricle from ultrasound images.
abstract: The segmentation of the left ventricle (LV) is an important task to assess the cardiac function in ultrasound images of the heart. This paper presents a novel methodology for the segmentation of the LV in three-dimensional (3-D) echocardiographic images based on the probabilistic data association filter (PDAF). The proposed methodology begins by initializing a 3-D deformable model either semiautomatically, with user input, or automatically, and it comprises the following feature hierarchical approach: 1) edge detection in the vicinity of the surface (low-level features); 2) edge grouping to obtain potential LV surface patches (mid-level features); and 3) patch filtering using a shape-PDAF framework (high-level features). This method provides good performance accuracy in 20 echocardiographic volumes, and compares favorably with the state-of-the-art segmentation methodologies proposed in the recent literature.
authors.forename: Carlos
authors.initials: C
authors.lastname: Santiago
authors.forename: Jacinto C
authors.initials: JC
authors.lastname: Nascimento
authors.forename: Jorge S
authors.initials: JS
authors.lastname: Marques
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004452:Echocardiography / Q000379:methods*; D004699:Endocardium / Q000000981:diagnostic imaging*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity