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Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models

Concetta Piazzese 1, 2 M. Chiara Carminati 3 Andrea Colombo 1 Rolf Krause 2 Mark Potse 2, 4 Angelo Auricchio 2 Lynn Weinert 5 Gloria Tamborini 3 Mauro Pepi 3 Roberto M Lang 5 Enrico G. Caiani 1 
3 Centro Cardiologico Monzino [Milano]
DISCCO - Dpt di Scienze Cliniche e di Comunità [Milano], IRCCS - Istituti di Ricovero e Cura a Carattere Scientifico
4 CARMEN - Modélisation et calculs pour l'électrophysiologie cardiaque
IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest, IHU-LIRYC
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 (r2 > 0.92) was found in all cases, with better results when using the SSM models comprising more than one frame of the cardiac cycle.
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Concetta Piazzese, M. Chiara Carminati, Andrea Colombo, Rolf Krause, Mark Potse, et al.. Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models. Journal of Electrocardiology, Elsevier, 2016, 49 (3), pp.383-391. ⟨10.1016/j.jelectrocard.2016.03.017⟩. ⟨hal-01302237⟩

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