Medical Image Clustering Algorithm Based on Graph Model
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    Abstract:

    Clustering algorithm of medical image is a significant part of special field image clustering. Due to technical limit and many problems in specific area, the study in this direction has been very challenging. The exiting algorithms of clustering require shape and density of data object, which imply that there won't be a good outcome for the application of medical image clustering. To solve the problem above, this paper firstly detects texture from image, proposes T-LBP method, divides the preprocessed image into multiple spaces, calculates the value of LBP spaces, and then builds a spatial sequence LBP histogram. In the end, the clustering method of MCST is proposed based on the created LBP histogram. The outcome of this experiment indicates that the algorithm presented in this paper achieved good results in terms of time complexity and clustering function.

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潘海为,谷井子,韩启龙,谢晓芹,张志强,荣晶施.基于图模型的医学图像聚类算法.软件学报,2013,24(S2):178-187

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History
  • Received:March 15,2013
  • Revised:July 11,2013
  • Adopted:
  • Online: January 02,2014
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