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Purpose: Echocardiography is commonly used as a non-invasive imaging tool inclinical practice for the assessment of cardiac function. However, delineationof the left ventricle is challenging due to the inherent properties ofultrasound imaging, such as the presence of speckle noise and the lowsignal-to-noise ratio. Methods: We propose a semi-automated segmentationalgorithm for the delineation of the left ventricle in temporal 3Dechocardiography sequences. The method requires minimal user interaction andrelies on a diffeomorphic registration approach. Advantages of the methodinclude no dependence on prior geometrical information, training data, orregistration from an atlas. Results: The method was evaluated usingthree-dimensional ultrasound scan sequences from 18 patients from theMazankowski Alberta Heart Institute, Edmonton, Canada, and compared to manualdelineations provided by an expert cardiologist and four other registrationalgorithms. The segmentation approach yielded the following results over thecardiac cycle: a mean absolute difference of 1.01 (0.21) mm, a Hausdorffdistance of 4.41 (1.43) mm, and a Dice overlap score of 0.93 (0.02).Conclusions: The method performed well compared to the four other registrationalgorithms.

A New Semi-Automated Algorithm for Volumetric Segmentation of the Left Ventricle in Temporal 3D Echocardiography Sequences