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  • Research Article
  • Open Access

Application of Artificial Immune System Approach in MRI Classification

EURASIP Journal on Advances in Signal Processing20082008:547684

https://doi.org/10.1155/2008/547684

Received: 30 November 2007

Accepted: 16 April 2008

Published: 30 April 2008

Abstract

Numerous scholars have submitted the theory and research of artificial immune systems (AISs) in recent years. Although AIS has been used in various fields, applying the AIS to medical images is very rare. The purpose of this study is using the clonal selection algorithm (CSA) of artificial immune systems for classifying the brain MRI, and displaying a single organism image which can finally offer faster organism reference information to a doctor; hence reducing the time to ascertain large number of images, so that the doctor can diagnose the nidus more efficiently and accurately. In order to verify the feasibility and efficiency of this method, we adopt statistical theory for manifold assessment and compare with the perceptron network of double layers, FCM method. The result proves that the method of this study is both feasible and useful.

Keywords

  • Manifold
  • Double Layer
  • Medical Image
  • System Approach
  • Statistical Theory

Publisher note

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Authors’ Affiliations

(1)
Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
(2)
Institute of Information and Electrical Energy, National Chin-Yi University of Technology, Taichung, Taiwan

Copyright

© Chuin-Mu Wang et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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