Abstract
A novel framework to efficiently deal with three-dimensional (3-D) segmentation of challenging inhomogeneous data in real-time has been recently introduced by the authors. However, the existing framework still relied on manual initialization, which prevented taking full advantage of the computational speed of the method. In the present article, an automatic initialization scheme adapted to 3-D, echocardiographic data is proposed. Moreover, a novel segmentation functional, which explicitly takes the darker appearance of the blood into account, is also introduced. The resulting automatic segmentation framework provides an efficient, fast and accurate solution for quantification of the main left ventricular volumetric indices used in clinical routine. In practice, the observed computation times are in the order of 1 s.
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