• DocumentCode
    575114
  • Title

    Unsupervised abdomen CT image segmentation using variable weight MRF in spatial and wavelet domain

  • Author

    Ma, Zhiyuan ; Jiang, Huiyan ; Yang, Benqiang ; Zhang, Libo

  • Author_Institution
    Software Coll., Northeastern Univ., Shenyang, China
  • fYear
    2011
  • fDate
    Nov. 29 2011-Dec. 1 2011
  • Firstpage
    915
  • Lastpage
    921
  • Abstract
    Aiming at the segmentation of liver image with fuzzy edge, a new algorithm based on Markov Random Field in spatial and wavelet domains is proposed. Firstly, a lifting wavelet transform is adopted to represent an original image in different resolutions; Secondly, attain the low frequency subimage and execute an initial segmentation and a multi-level segmentation; Lastly, the spatial domain transform is applied on the segmentation result of the wavelet domain to revise the segmentation results and to get an accurate outcome. The algorithms of the initial and multi-level segmentation in wavelet domain are K-means improved by SAPSO and MAP/ICM. Experimental results show that the proposed algorithm has a good robustness.
  • Keywords
    Markov processes; computerised tomography; fuzzy set theory; image segmentation; medical image processing; wavelet transforms; K-means; MAP-ICM; Markov random field; SAPSO; fuzzy edge; lifting wavelet transform; liver image segmentation; multilevel segmentation; spatial domain transform; unsupervised abdomen CT image segmentation; variable weight MRF; wavelet domain; Computed tomography; Equations; Image segmentation; Mathematical model; Wavelet domain; Wavelet transforms; Abdomen CT imag; ICM; Image segmentation; MAP; Markov Random Field; Simulated Annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
  • Conference_Location
    Seogwipo
  • Print_ISBN
    978-1-4577-0472-7
  • Type

    conf

  • Filename
    6316750