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.

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

PIAZZESE, CONCETTA;CAIANI, ENRICO GIANLUCA
2016

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.
Cardiac MRI; Image segmentation; Left ventricular volume; Statistical shape model; Cardiology and Cardiovascular Medicine
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1012502
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