• Title of article

    Detection of malignant Cases by Segmentation of Cells in Medical Images and Applying Fuzzy Logic Technique

  • Author/Authors

    attia, salim j. baghdad university - college of dentistry, iraq , abood, ziad m. almustasiriyah university - college of education, Iraq , agool, ibrahim r. almustasiriyah university - college of science, iraq

  • From page
    71
  • To page
    74
  • Abstract
    The process of detection and segmentation of cells is considered in digital optical images of human breast tissue as important base to diagnose the diseases. The major features of malignancy are related with the cells. It is therefore essential to operate a segmentation of the image, to isolate the cells from the rest of image, i. e., from other tissue components, and from some other undesirable elements of images. The recognition process includes a segmentation algorithm based on an adaptive imaging threshold procedure that is sensitive to local ranges in pixel intensity (minimum-maximum values). The statistical features are extracted from the images of cells like median, mode, mean and standard deviation. Then the fuzzy logic method is applied to detect breast cancer.
  • Keywords
    segmentation , adaptive threshold , optical imaging , fuzzy logic
  • Journal title
    Journal of Thi-Qar Science
  • Journal title
    Journal of Thi-Qar Science
  • Record number

    2724701