Segmentation of 3D echocardiographic images using deformable simplex meshes and adaptive filtering

Semi-automatic segmentation of the heart muscle in three-dimensional (3D) echographic images may substantially support clinical diagnosis of (congenital) heart disease. It may serve as an important preprocessing step for automated cardiac strain imaging and could be used for cardiac output measurement. Echocardiographic image sequences of the left ventricle of one healthy subject and one piglet were obtained in radiofrequency (rf) format, directly after beamforming, in Full Volume mode. 3D Adaptive Mean Squares (AMS) filtering was performed on the demodulated rf-data to optimize the distinction between blood and myocardium. A 3D deformable simplex mesh was then used to segment the endocardial surface. A gradient and a speed force were included as external forces of the model. Initial results show that segmentation of the endocardial surface using 3D deformable simplex meshes in combination with adaptive filtering is feasible. Cardiac output (CO) measurements in the piglet model, based on this segmentation technique were promising. The method can be applied to non-standard heart geometries without having to impose strong shape constraints.