Boundary Detection in Echocardiographic Images Using Markovian Level Set Method

Jierong CHENG  Say-Wei FOO  

IEICE TRANSACTIONS on Information and Systems   Vol.E90-D   No.8   pp.1292-1300
Publication Date: 2007/08/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e90-d.8.1292
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
echocardiographic images,  segmentation,  boundary detection,  MRF,  level set,  

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Owing to the large amount of speckle noise and ill-defined edges present in echocardiographic images, computer-based boundary detection of the left ventricle 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 Markov random field (MRF) model, which makes use of local statistics with level set method that handles topological changes, to detect a continuous and smooth boundary. Experimental results show that higher accuracy can be achieved with the proposed method compared with two related MRF-based methods.