• DocumentCode
    259334
  • Title

    Detection of Mammograms Using Honey Bees Mating Optimization Algorithm (M-HBMO)

  • Author

    Durgadevi, R. ; Hemalatha, B. ; Kaliappan, K. Vishnu Kumar

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Jansons Inst. of Technol., Coimbatore, India
  • fYear
    2014
  • fDate
    Feb. 27 2014-March 1 2014
  • Firstpage
    50
  • Lastpage
    53
  • Abstract
    Mammography is the best available technique used by radiologists for screening early detection of breast cancer. In digital mammography the crisis of finding efficient and precise breast profile segmentation technique is time-consuming. In this research work, a novel hybrid method named M-HBMO (Mammogram based Honey Bees Mating Optimization) algorithm has been proposed to segment the lesion. The cancer profile segmentation is based on texture feature and extraction of the lesion. The M-HBMO is evaluated with conventional ROI (region of interest) Algorithm. The experiment is conducted with MRI images retrieved from the medical hospital database. The result proves that the M-HBMO method segments the breast region accurately correspond to respective MRI images.
  • Keywords
    biological tissues; cancer; diagnostic radiography; feature extraction; image segmentation; image texture; mammography; medical image processing; optimisation; M-HBMO; MRI image; ROI algorithm; breast cancer early detection; breast profile segmentation technique; breast region; cancer profile segmentation; digital mammography; hybrid method; lesion extraction; lesion segmentation; mammogram based honey bees mating optimization algorithm; mammogram detection; medical hospital database; radiology; region of interest algorithm; texture feature; Breast cancer; Image segmentation; Magnetic resonance imaging; Noise; Wiener filters; Filter; HBMO; Mammograms; ROI; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing and Communication Technologies (WCCCT), 2014 World Congress on
  • Conference_Location
    Trichirappalli
  • Print_ISBN
    978-1-4799-2876-7
  • Type

    conf

  • DOI
    10.1109/WCCCT.2014.52
  • Filename
    6755104