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  • 标题:Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration
  • 本地全文:下载
  • 作者:Chengcai Leng ; Jinjun Xiao ; Min Li
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2015
  • 卷号:2015
  • DOI:10.1155/2015/829528
  • 出版社:Hindawi Publishing Corporation
  • 摘要:This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images.
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