title: Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models.
abstract: We evaluate in this paper different strategies for the construction of a statistical shape model (SSM) of the left ventricle (LV) to be used for segmentation in cardiac magnetic resonance (CMR) images. From a large database of LV surfaces obtained throughout the cardiac cycle from 3D echocardiographic (3DE) LV images, different LV shape models were built by varying the considered phase in the cardiac cycle and the registration procedure employed for surface alignment. Principal component analysis was computed to describe the statistical variability of the SSMs, which were then deformed by applying an active shape model (ASM) approach to segment the LV endocardium in CMR images of 45 patients. Segmentation performance was evaluated by comparing LV volumes derived by ASM segmentation with different SSMs and those obtained by manual tracing, considered as a reference. A high correlation (r(2)>0.92) was found in all cases, with better results when using the SSM models comprising more than one frame of the cardiac cycle.
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy; Centre for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland. Electronic address: concetta.piazzese@polimi.it.
authors.forename: Concetta
authors.initials: C
authors.lastname: Piazzese
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy.
authors.forename: M Chiara
authors.initials: MC
authors.lastname: Carminati
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Colombo
authors.affiliation: Centre for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland.
authors.forename: Rolf
authors.initials: R
authors.lastname: Krause
authors.affiliation: Centre for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland; Inria Bordeaux Sud-Ouest, Talence, France.
authors.forename: Mark
authors.initials: M
authors.lastname: Potse
authors.affiliation: Centre for Computational Medicine in Cardiology, Institute of Computational Science, Università della Svizzera italiana, Lugano, Switzerland.
authors.forename: Angelo
authors.initials: A
authors.lastname: Auricchio
authors.affiliation: Department of Cardiology, University of Chicago, IL, USA.
authors.forename: Lynn
authors.initials: L
authors.lastname: Weinert
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy.
authors.forename: Gloria
authors.initials: G
authors.lastname: Tamborini
authors.affiliation: Centro Cardiologico Monzino IRCCS, Milan, Italy.
authors.forename: Mauro
authors.initials: M
authors.lastname: Pepi
authors.affiliation: Department of Cardiology, University of Chicago, IL, USA.
authors.forename: Roberto M
authors.initials: RM
authors.lastname: Lang
authors.affiliation: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy.
authors.forename: Enrico G
authors.initials: EG
authors.lastname: Caiani
mesh_terms: D003198:Computer Simulation; D004452:Echocardiography / Q000379:methods*; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D004699:Endocardium / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D018487:Ventricular Dysfunction, Left / Q000000981:diagnostic imaging* / Q000473:pathology
keywords: Cardiac MRI; Image segmentation; Left ventricular volume; Statistical shape model