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BIOMEDICAL IMAGE PROCESSING USING COMBINED MRF-CNN METHOD

Journal Name:

  • Istanbul University Journal of Electrical & Electronics Engineering

Publication Year:

  • 2004

Key Words:

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this paper, to improve image performance of biomedical data, Markov Random Field (MRF) and Cellular Neural Network (CNN) structures are combined and a new approach, Markov Random Field-Cellular Neural Networks (MRF-CNN) is introduced. MRF-CNN structure can be applied to biomedical data for various image processing problems such as noise filtering, edge detecting, blank filing etc., with noise variance up to 9 dB and better results are obtained according to MRF and CNN schemes. In training of MRF-CNN, Recursive Perceptron Learning Algorithms (RPLA) is studied.
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FULL TEXT (PDF): 
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  • 2
1227-1231
  • English

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