Abstract
Three-dimensional ultrasound is emerging as a viable resource for the imaging of internal organs. Quantitative studies correlating ultrasonic volume measurements with MRI data continue to validate this modality as a more efficient alternative for 3D imaging studies. However, the processing required to form 3D images from a set of 2D images may result in a loss of spatial resolution and may give rise to artifacts. This paper examines a method of automatic feature extraction and data quantification in 3D data sets as compared with original 2D data. This work will implement an active contour algorithm to automatically extract the endocardial borders of septal defects in echocardiographic images, and compare the size of the defects in the original 2D images and the 3D data sets.
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