title: Automatic segmentation of echocardiographic sequences by active appearance motion models.
abstract: A novel extension of active appearance models (AAMs) for automated border detection in echocardiographic image sequences is reported. The active appearance motion model (AAMM) technique allows fully automated robust and time-continuous delineation of left ventricular (LV) endocardial contours over the full heart cycle with good results. Nonlinear intensity normalization was developed and employed to accommodate ultrasound-specific intensity distributions. The method was trained and tested on 16-frame phase-normalized transthoracic four-chamber sequences of 129 unselected infarct patients, split randomly into a training set (n = 65) and a test set (n = 64). Borders were compared to expert drawn endocardial contours. On the test set, fully automated AAMM performed well in 97% of the cases (average distance between manual and automatic landmark points was 3.3 mm, comparable to human interobserver variabilities). The ultrasound-specific intensity normalization proved to be of great value for good results in echocardiograms. The AAMM was significantly more accurate than an equivalent set of two-dimensional AAMs.
authors.affiliation: Division of Image Processing (LKEB), Department of Radiology, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands. j.g.bosch@lumc.nl
authors.forename: Johan G
authors.initials: JG
authors.lastname: Bosch
authors.forename: Steven C
authors.initials: SC
authors.lastname: Mitchell
authors.forename: Boudewijn P F
authors.initials: BP
authors.lastname: Lelieveldt
authors.forename: Francisca
authors.initials: F
authors.lastname: Nijland
authors.forename: Otto
authors.initials: O
authors.lastname: Kamp
authors.forename: Milan
authors.initials: M
authors.lastname: Sonka
authors.forename: Johan H C
authors.initials: JH
authors.lastname: Reiber
mesh_terms: D000465:Algorithms; D004452:Echocardiography / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D009038:Motion; D009203:Myocardial Infarction / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016037:Single-Blind Method