Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration
Joint Authors
Leng, Chengcai
Xiao, Jinjun
Li, Min
Zhang, Haipeng
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-19
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Leng, Chengcai& Xiao, Jinjun& Li, Min& Zhang, Haipeng. 2015. Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration. Computational Intelligence and Neuroscience،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1057766
Modern Language Association (MLA)
Leng, Chengcai…[et al.]. Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration. Computational Intelligence and Neuroscience No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1057766
American Medical Association (AMA)
Leng, Chengcai& Xiao, Jinjun& Li, Min& Zhang, Haipeng. Robust Adaptive Principal Component Analysis Based on Intergraph Matrix for Medical Image Registration. Computational Intelligence and Neuroscience. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1057766
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1057766