Segmentation of the left ventricular endocardium from magnetic resonance images by using different statistical shape models
PIAZZESE, Concetta
Politecnico di Milano [Milan] [POLIMI]
Center for Computational Medicine in Cardiology [Lugano]
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Politecnico di Milano [Milan] [POLIMI]
Center for Computational Medicine in Cardiology [Lugano]
PIAZZESE, Concetta
Politecnico di Milano [Milan] [POLIMI]
Center for Computational Medicine in Cardiology [Lugano]
Politecnico di Milano [Milan] [POLIMI]
Center for Computational Medicine in Cardiology [Lugano]
POTSE, Mark
Center for Computational Medicine in Cardiology [Lugano]
Modélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
< Leer menos
Center for Computational Medicine in Cardiology [Lugano]
Modélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
Idioma
en
Article de revue
Este ítem está publicado en
Journal of Electrocardiology. 2016-05-01, vol. 49, n° 3, p. 383–391
Elsevier
Resumen en inglés
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 ...Leer más >
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.< Leer menos
Palabras clave en inglés
Cardiac MRI
Image segmentation
Left ventricular volume
Statistical shape model
Orígen
Importado de HalCentros de investigación