title: Automatic delineation of the myocardial wall from CT images via shape segmentation and variational region growing.
abstract: Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this paper, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images.
authors.forename: Liangjia
authors.initials: L
authors.lastname: Zhu
authors.forename: Yi
authors.initials: Y
authors.lastname: Gao
authors.forename: Vikram
authors.initials: V
authors.lastname: Appia
authors.forename: Anthony
authors.initials: A
authors.lastname: Yezzi
authors.forename: Chesnal
authors.initials: C
authors.lastname: Arepalli
authors.forename: Tracy
authors.initials: T
authors.lastname: Faber
authors.forename: Arthur
authors.initials: A
authors.lastname: Stillman
authors.forename: Allen
authors.initials: A
authors.lastname: Tannenbaum
mesh_terms: D000465:Algorithms; D000818:Animals; D004699:Endocardium / Q000000981:diagnostic imaging*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013552:Swine; D014057:Tomography, X-Ray Computed / Q000379:methods*