Echocardiographic Simulation for Validation of Automated Segmentation Methods

Segmentation of echocardiographic imagery is central to the understanding, diagnosis, and treatment of cardiovascular disease. Although volumes of literature have been devoted to automated image segmentation, little work has been directed towards the validation of these techniques. An echocardiographic simulation has the advantage of exact knowledge of the myocardial borders, thus providing quantifiable measurements of an algorithms performance. Existing simulation tools either become intractable when generating multiple images, or accommodate only simplistic myocardial motion models. This paper proposes a novel tool for the simulation of short-axis echocardiographic image sequences towards the goal of automated segmentation algorithm validation. We consider a complete set of simulation concerns, including a realistic myocardial model, variable inter-frame speckle pattern correlation, and low computational cost for fast simulation. We demonstrate the value of the proposed tool by evaluating a speckle filtering algorithms effects on segmentation accuracy.