AGPU 3D segmentation framework for medical imaging

Abstract

In this work we propose a fast and flexible GPU 3D level-set segmentation framework able to handle different segmentation tasks. Experiments on simulated and real images demonstrate the method ability at achieving high computational efficiency with no reduction in segmentation accuracy compared to its sequential counterpart. The method clinical applicability is demonstrated by addressing the task of Left-Ventricle myocardium segmentation in Real-Time 3D Echocardiography.