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]
< Reduce
Center for Computational Medicine in Cardiology [Lugano]
Modélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
Language
en
Article de revue
This item was published in
Journal of Electrocardiology. 2016-05-01, vol. 49, n° 3, p. 383–391
Elsevier
English 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 ...Read more >
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.Read less <
English Keywords
Cardiac MRI
Image segmentation
Left ventricular volume
Statistical shape model
Origin
Hal imported