title: Contour tracking in echocardiographic sequences via sparse representation and dictionary learning.
abstract: This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets.
authors.affiliation: Department of Electrical Engineering, Yale University, New Haven, CT 06520, USA. Electronic address: xiaojie.huang@yale.edu.
authors.forename: Xiaojie
authors.initials: X
authors.lastname: Huang
authors.affiliation: Department of Internal Medicine, Yale University, New Haven, CT 06520, USA.
authors.forename: Donald P
authors.initials: DP
authors.lastname: Dione
authors.affiliation: Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.
authors.forename: Colin B
authors.initials: CB
authors.lastname: Compas
authors.affiliation: Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA.
authors.forename: Xenophon
authors.initials: X
authors.lastname: Papademetris
authors.affiliation: Department of Internal Medicine, Yale University, New Haven, CT 06520, USA.
authors.forename: Ben A
authors.initials: BA
authors.lastname: Lin
authors.affiliation: Department of Internal Medicine, Yale University, New Haven, CT 06520, USA.
authors.forename: Alda
authors.initials: A
authors.lastname: Bregasi
authors.affiliation: Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA; Department of Internal Medicine, Yale University, New Haven, CT 06520, USA.
authors.forename: Albert J
authors.initials: AJ
authors.lastname: Sinusas
authors.affiliation: Department of Electrical Engineering, Yale University, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA.
authors.forename: Lawrence H
authors.initials: LH
authors.lastname: Staib
authors.affiliation: Department of Electrical Engineering, Yale University, New Haven, CT 06520, USA; Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA; Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA.
authors.forename: James S
authors.initials: JS
authors.lastname: Duncan
mesh_terms: D000465:Algorithms; D000818:Animals; D016477:Artifacts; D004285:Dogs; D004452:Echocardiography / Q000379:methods*; D004699:Endocardium / Q000000981:diagnostic imaging; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D009203:Myocardial Infarction / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Contour tracking; Dictionary learning; Echocardiography; Segmentation; Sparse representation