title: Robust physically-constrained modeling of the mitral valve and subvalvular apparatus.
abstract: Mitral valve (MV) is often involved in cardiac diseases, with various pathological patterns that require a systemic view of the entire MV apparatus. Due to its complex shape and dynamics, patient-specific modeling of the MV constitutes a particular challenge. We propose a novel approach for personalized modeling of the dynamic MV and its subvalvular apparatus that ensures temporal consistency over the cardiac sequence and provides realistic deformations. The idea is to detect the anatomical MV components under constraints derived from the biomechanical properties of the leaflets. This is achieved by a robust two-step alternate algorithm that combines discriminative learning and leaflet biomechanics. Extensive evaluation on 200 transesophageal echochardiographic sequences showed an average Hausdorff error of 5.1 mm at a speed of 9 sec, which constitutes an improvement of up to 11.5% compared to purely data driven approaches. Clinical evaluation on 42 subjects showed, that the proposed fully-automatic approach could provide discriminant biomarkers to detect and quantify remodeling of annulus and leaflets in functional mitral regurgitation.
authors: Image Analytics and Informatics, Siemens Corporate Research, Princeton, USA.
authors: Ingmar
authors: I
authors: Voigt
authors: Tommaso
authors: T
authors: Mansi
authors: Razvan Ioan
authors: RI
authors: Ionasec
authors: Etienne Assoumou
authors: EA
authors: Mengue
authors: Helene
authors: H
authors: Houle
authors: Bogdan
authors: B
authors: Georgescu
authors: Joachim
authors: J
authors: Hornegger
authors: Dorin
authors: D
authors: Comaniciu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001331:Automation; D001696:Biomechanical Phenomena; D017548:Echocardiography, Transesophageal / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008943:Mitral Valve / Q000033:anatomy & histology / Q000473:pathology*; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated; D012984:Software