• DocumentCode
    3155060
  • Title

    Adaptation of Region Growing thresholds using Memetic Programming algorithm

  • Author

    Ayman, Ahmed ; Mabrouk, Emad ; Elnomery, Zanaty

  • Author_Institution
    Fac. of Sci., Al-Azhar Univ., Assiut, Egypt
  • fYear
    2013
  • fDate
    16-20 June 2013
  • Firstpage
    29
  • Lastpage
    34
  • Abstract
    This paper presents a new strategy for the segmentation of brain images from the volumetric Magnetic Resonance Imaging (MRI). We propose a new segmentation technique that hybridize an evolutionary algorithm, called the Memetic Programming (MP) algorithm, with the Region Growing (RG) technique. The MP algorithm generates new threshold functions and then the RG uses these thresholds to perform an efficient segmentation of MRI images. The proposed segmentation technique are tested through a set of medical images with different noise and Radio Frequency (RF) levels. The experimental results show that the proposed technique produces more accurate and promising results.
  • Keywords
    biomedical MRI; brain; evolutionary computation; image segmentation; medical image processing; MP algorithm; MRI; RG technique; brain image segmentation; evolutionary algorithm; memetic programming algorithm; radio frequency; region growing threshold adaptation; volumetric magnetic resonance imaging; Biomedical imaging; Image segmentation; Magnetic resonance imaging; Noise; Radio frequency; Sociology; Statistics; Automatic Threshold; Brain MRI; Medical Image Segmentation; Memetic Programming; Region Growing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2013 IEEE/ACIS 12th International Conference on
  • Conference_Location
    Niigata
  • Type

    conf

  • DOI
    10.1109/ICIS.2013.6607812
  • Filename
    6607812