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A Novel CT Image Dynamic Fuzzy Retrieval Method Using Curvelet Transform

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High Performance Computing and Applications

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5938))

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Abstract

Curvelet transform as time-frequency and multiresolution analysis tool is often used in the domain of image processing, especially for image characteristic extraction. This paper proposes a novel CT image retrieval method which is combining curvelet transform and dynamic fuzzy theory. Firstly, the image was decomposed by curvelet transform to obtain the different subbands coefficients. Then the entropy from certain subband was calculated, and a membership function based on dynamic fuzzy theory was constructed to adjust the weight of coefficients similarity. At last a model was constructed to obtain the similarity degree for CT image retrieval. The precision of our model could be applied to CT image retrieval practically.

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References

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Author information

Authors and Affiliations

  1. The Institute of Intelligent Information Processing and Application, Soochow University, Suzhou, 215006, China

    Guangming Zhang, Zhiming Cui & Shengrong Gong

  2. JiangSu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise, Suzhou, 215104, China

    Zhiming Cui

Authors
  1. Guangming Zhang
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  2. Zhiming Cui
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  3. Shengrong Gong
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Editor information

Editors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, 200072, Shanghai, P.R. China

    Wu Zhang  & Weiqin Tong  & 

  2. Schulich School of Engineering, University of Calgary, T2N 1N4, Calgary, AB, Canada

    Zhangxin Chen

  3. Department of Mathematics, University of Wyoming, 1000 University Avenue, 82071-3036, Laramie, WY, USA

    Craig C. Douglas

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© 2010 Springer-Verlag Berlin Heidelberg

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Zhang, G., Cui, Z., Gong, S. (2010). A Novel CT Image Dynamic Fuzzy Retrieval Method Using Curvelet Transform. In: Zhang, W., Chen, Z., Douglas, C.C., Tong, W. (eds) High Performance Computing and Applications. Lecture Notes in Computer Science, vol 5938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11842-5_78

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  • DOI: https://doi.org/10.1007/978-3-642-11842-5_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11841-8

  • Online ISBN: 978-3-642-11842-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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