Markovian level set for echocardiographic image segmentation

Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle (LV) has proved to be a challenging problem. In this paper, a Markovian level set method for boundary detection in long-axis echocardiographic images is proposed. It combines MRF model which makes use of local statistics with level set method which handles topological changes, to detect a continuous and smooth LV boundary. Experimental results show that high accuracy is achieved with the proposed method. The experimental results are also compared with two related MRF-based methods to demonstrate its superiority

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