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Medical Image Clustering Algorithm Based on Graph Model

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 405))

Abstract

The algorithm of medical image is an important part of special field image clustering. There are many problems of technical aspects and the problem of specific area, so that the study of this direction is very challenging. The existing algorithm of clustering has requirement about shape and density of data object, and it cannot get a good result to the application of medical image clustering. In view of the above problem and under the guidance of knowledge of medical image, at first, detects texture from image, and T-LBP method is put forward. Then divides the preprocessed image into many spaces, and calculates LBP value of spaces. At last build spatial sequence LBP histogram. Based on the LBP histogram, the clustering method of MCST is proposed. The result of experiment shows that there are good result at time complexity and clustering result in the algorithm of this paper.

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Pan, H., Gu, J., Han, Q., Feng, X., Xie, X., Li, P. (2014). Medical Image Clustering Algorithm Based on Graph Model . In: Li, K., Xiao, Z., Wang, Y., Du, J., Li, K. (eds) Parallel Computational Fluid Dynamics. ParCFD 2013. Communications in Computer and Information Science, vol 405. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53962-6_5

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  • DOI: https://doi.org/10.1007/978-3-642-53962-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53961-9

  • Online ISBN: 978-3-642-53962-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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