Boundary Detection in Echocardiographic Images Using Markovian Level Set Method
| Autor: | Jierong Cheng, Say Wei Foo |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Level set (data structures)
Markov random field Level set method business.industry Boundary (topology) Speckle noise Markov model Edge detection Speckle pattern Artificial Intelligence Hardware and Architecture Computer vision Computer Vision and Pattern Recognition Artificial intelligence Electrical and Electronic Engineering business Algorithm Software Mathematics |
| Zdroj: | IEICE Transactions on Information and Systems. :1292-1300 |
| ISSN: | 1745-1361 0916-8532 |
| DOI: | 10.1093/ietisy/e90-d.8.1292 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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