• DocumentCode
    2612096
  • Title

    Lungs Nodule Detection by Using Fuzzy Morphology from CT Scan Images

  • Author

    Jaffar, M. Arfan ; Hussain, Ayyaz ; Mirza, Anwar M.

  • Author_Institution
    Dept. of Comput. Sci., FAST Nat. Univ. of Comput. & Emerging Sci., Islamabad, Pakistan
  • fYear
    2009
  • fDate
    17-20 April 2009
  • Firstpage
    57
  • Lastpage
    61
  • Abstract
    In this paper we have proposed a method for lungs nodule detection from computed tomography (CT) scanned images by using Fuzzy C-Mean (FCM) and morphological techniques. First of all, fuzzy have been used for automated segmentation of lungs. Region of interests (ROIs) have been extracted by using 8 directional searches slice by slice and then 3D ROI image have been constructed. A 3D template has been constructed and convolves with the 3D ROI image. Finally FCM have been used to extract ROI that contain nodule. The proposed system is capable to perform fully automatic segmentation and nodule detection from CT Scan Lungs images, based solely on information contained by the image itself. The technique was tested against the 50 datasets of different patients received from Aga Khan Medical University, Pakistan and Lung Image Database Consortium (LIDC) dataset.
  • Keywords
    computerised tomography; fuzzy logic; image segmentation; lung; medical image processing; 3D ROI image; CT scan images; automated segmentation; computed tomography; fuzzy morphology; lungs nodule detection; Cancer detection; Computed tomography; Computer science; Data mining; Entropy; Image segmentation; Lungs; Morphology; Shape; Springs; computer aided diagnosis; mathematical morphology; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology - Spring Conference, 2009. IACSITSC '09. International Association of
  • Conference_Location
    Singapore
  • Print_ISBN
    978-0-7695-3653-8
  • Type

    conf

  • DOI
    10.1109/IACSIT-SC.2009.89
  • Filename
    5169310