Earticle

초록

영어

With the rapid advancement of the computer assisted medical applications, the MRI image segmentation has been a hottest research topic. In the neural network is used for the image segmentation, we need a lot of training data, because of the large amount of the data, computing speed is quite slow, not suitable for real-time data processing, lead to the low resolution image segmentation, the resolution is not high, this paper proposes a fuzzy image segmentation algorithm of the BP neural network. Fuzzy set theory is used to subtract the characteristics after area of the image segmentation, reduce the dimension of feature vector. We adopt the revised neural network to undertake the experimental simulation compared with the other state-of-the-art approaches. The result proves the effectiveness of our methodology. Our algorithm could segment the regions of interest with the ability of eliminating the out side noise which achieves the better robustness.

목차

Abstract
 1. Introduction
 2. The Proposed Algorithm
  2.1. The Review of MRI (Magnetic Resonance Imaging) Images
  2.2. The Traditional BP Neural Network
  2.3. The Fuzzy based BP Neural Network
  2.4. The Novel Image Segmentation Framework
 3. Experimental Simulation and Verification
 4. Conclusion
 References

키워드

저자

• Jie Yang [ School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China ]
• Xiaoling Guo [ School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China ]
• Xiao Zhang [ School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China ] Corresponding Author
• Jingjing Yang [ School of Information Science and Engineering, Hebei North University, Zhangjiakou, Hebei, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605