Boundary Detection in Echocardiographic Images Using Markovian Level Set Method(Image Recognition, Computer Vision)

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概要

• 論文の詳細を見る

• 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.

• 社団法人電子情報通信学会の論文
• 2007-08-01

著者

• Foo Say-wei

  School Of Electrical And Electronic Engineering Nanyang Technological University

• Foo Say-wei

  School Of Eee Nanyang Technological University

• CHENG Jierong

  School of Electrical and Electronic Engineering, Nanyang Technological University

• Cheng Jierong

  School Of Electrical And Electronic Engineering Nanyang Technological University

関連論文

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• Level-Building on AdaBoost HMM Classifiers and the Application to Visual Speech Processing(Speech and Hearing)
• Boundary Detection in Echocardiographic Images Using Markovian Level Set Method(Image Recognition, Computer Vision)
• Speaker Recognition Using Adaptively Boosted Classifiers (Special Issue on Speech Information Processing)

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