• DocumentCode
    2716997
  • Title

    Lung Nodule Diagnosis from CT Images Using Fuzzy Logic

  • Author

    Samuel, C. Clifford ; Saravanan, V. ; Devi, M. R Vimala

  • Author_Institution
    VIT Univ., Vellore
  • Volume
    3
  • fYear
    2007
  • fDate
    13-15 Dec. 2007
  • Firstpage
    159
  • Lastpage
    163
  • Abstract
    In this paper we present a technique for recognizing the lung nodules for different diagnosis of lung cancer based on CT images. Nodule detection is carried in the following steps: preprocessing using wavelet technique, biorthogonal wavelet is used for image enhancement. The enhanced image is subjected to Bi-Histogram equalization. The resultant image is more accurate and sharp. The enhanced image is binarised using the thresholding. Then the binarised image is subjected to Morphological transform. The filtered image is segmented and features are extracted. The extracted features are given to the fuzzy inference systems (FIS). The fuzzy system finds the severity of the lung nodules based on the IF-THEN rules.
  • Keywords
    computerised tomography; fuzzy logic; fuzzy reasoning; image enhancement; medical image processing; wavelet transforms; CT images; bihistogram equalization; biorthogonal wavelet; features extraction; fuzzy inference systems; fuzzy logic; image enhancement; lung cancer; lung nodule diagnosis; morphological transform; nodule detection; wavelet technique; Cancer detection; Computed tomography; Fuzzy logic; Fuzzy systems; Image enhancement; Image reconstruction; Image segmentation; Lungs; Morphology; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Conference on Computational Intelligence and Multimedia Applications, 2007. International Conference on
  • Conference_Location
    Sivakasi, Tamil Nadu
  • Print_ISBN
    0-7695-3050-8
  • Type

    conf

  • DOI
    10.1109/ICCIMA.2007.236
  • Filename
    4426360