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Echocardiograms are acquired from standard views to ensure correct assessment of cardiac function. There is an increasing use of quantitative tools where specific views are required. Further, non-expert users of echocardiography are increasing, and thus a need for quality assurance during imaging. The aim of this project is to develop automatic and robust real-time classification of cardiac views...
This work presents an algorithm capable of classifying an echocardiographic view as either an apical two chamber view, four chamber view or long axis view. It also provides a score on the overall image quality. The algorithm is based on a deformable non uniform rational B-spline (NURBS) model updated in an extended Kalman filter framework. Models are constructed for each of the three standard views...
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