• DocumentCode
    3472318
  • Title

    Ordered-subsets EM algorithm for image segmentation with application to brain MRI

  • Author

    Hashimoto, Aiko ; Kudo, Hiroyuiti

  • Author_Institution
    Doctral Program in Eng., Tsukuba Univ., Ibaraki, Japan
  • Volume
    3
  • fYear
    2000
  • fDate
    2000
  • Abstract
    Proposes a fast expectation maximization (EM) algorithm called the ordered-subsets EM (OS-EM) algorithm for statistical model-based image segmentation. The OS-EM algorithm is based on the ordered-subsets idea which has been successfully used for image reconstruction in SPECT and PET. The OS-EM algorithm is very simple such that one needs only a few small changes in the code of the EM algorithm. The authors have applied the OS-EM algorithm to brain MRI images obtained from the MRI simulator. The results demonstrate that the OS-EM algorithm rapidly converges to a reasonable approximate solution with few iterations. Furthermore, there is no significant difference between the segmentation result with the EM algorithm and that with the OS-EM algorithm
  • Keywords
    biomedical MRI; brain; image reconstruction; image segmentation; medical image processing; optimisation; statistics; MRI simulator; PET; SPECT; brain MRI; iterations; magnetic resonance imaging; medical diagnostic imaging; ordered-subsets EM algorithm; statistical model-based image segmentation; Bayesian methods; Biomedical imaging; Brain modeling; Clustering algorithms; Image converters; Image reconstruction; Image segmentation; Iterative algorithms; Magnetic resonance imaging; Positron emission tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium Conference Record, 2000 IEEE
  • Conference_Location
    Lyon
  • ISSN
    1082-3654
  • Print_ISBN
    0-7803-6503-8
  • Type

    conf

  • DOI
    10.1109/NSSMIC.2000.949249
  • Filename
    949249