• DocumentCode
    2690642
  • Title

    Computer simulation for segmentation of lung nodules in CT images

  • Author

    Dajnowiec, Maciej ; Alirezaie, Javad

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, Ont.
  • Volume
    5
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    4491
  • Abstract
    Automated lung nodule detection through computed tomography (CT) image segmentation is a new and exciting research area of medical image processing. We are currently developing a nodule detection system. For the testing stage we have developed a method to insert simulated lung nodules into CT images. The simulated nodules can be used to produce corner cases to provide a better test environment for the segmentation technique than would be available through clinical data. The synthetic lung nodules produced by this program are based on a 2D Gaussian structure. This is modeled on the study of the structure of real lung nodules. We have also developed a lung segmentation technique, which is the first stage of our nodule detection system. The lungs are segmented using a combination of thresholding, morphology, 3D region growing, and volume analysis
  • Keywords
    Gaussian processes; computerised tomography; image segmentation; lung; medical image processing; 2D Gaussian structure; CT images; computed tomography image segmentation; lung nodules segmentation; medical image processing; nodule detection system; Cancer detection; Computational modeling; Computed tomography; Computer simulation; Diagnostic radiography; Image segmentation; Lungs; Medical simulation; Robustness; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics, 2004 IEEE International Conference on
  • Conference_Location
    The Hague
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-8566-7
  • Type

    conf

  • DOI
    10.1109/ICSMC.2004.1401239
  • Filename
    1401239