Earticle

초록

영어

It is hard to segmentation brain MR images for the bias fields. In this paper, a new fuzzy anisotropic diffusion function is presented to reduce the effect of the noise. We use Legendre polynomial functions to reconstruct the bias field, which make the entropy of the recovered image be smallest. But it needs to compute a lot of parameters to reconstruct the bias. The traditional method uses the gradient descending method to compute the parameters. The method plunges into local best easily. In order to deal with this problem, Particle swarm optimization (PSO) method is analyzed. A new particle swarm technique is proposed that incorporates initial location information and use mutate operation make the particles away from local maxima. The experiments show that the new method can get accurate result robustly.

목차

Abstract
 1. Introduction
 2. Methods
  2.1. Skull Stripping
  2.2. Fuzzy Anisotropic Diffusion Function
  2.3. Bias Field Model
  2.4. Entropy Optimization
  2.5. Algorithm Parameters
 3. Implementation and Results
 4. Conclusion
 Acknowledgements
 5. References
  5.1. Journal Article
  5.2. Conference Proceedings

키워드

저자

• Yunjie Chen [ School of math and statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Yingying Chu [ School of math and statistics, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Jin Wang [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China ]
• Yuhui Zheng [ School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, 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