• DocumentCode
    1883664
  • Title

    Research on medical image retrieval based on texture feature

  • Author

    Wang Mingquan ; Cai Guohua ; Zhang Shi

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2012
  • fDate
    12-15 Aug. 2012
  • Firstpage
    51
  • Lastpage
    54
  • Abstract
    Feature extraction is one of the most important steps in content-based medical image retrieval (CBMIR). In this paper, we propose a new method of improved Gray Level Co-occurrence Matrix (GLCM). In this method, we apply the Gradient Phase Mutual Information (GP-MI) combined with the method of masked image to overcome the shortcoming that the traditional GLCM is impacted greatly by the rotation angle and the background region. The method of GP-MI is applied to compute the angle between two images and the method of masked image is applied to remove the background of the image. After these two steps, we divide the image into several blocks equally and calculate the GLCM of every block. Then we sum the GLCM of every block by different weights as the final texture feature. Lastly medical image retrieval was executed according to the similarity calculation. The results of the test indicate that the proposed method has a promising effect.
  • Keywords
    content-based retrieval; feature extraction; image retrieval; image texture; matrix algebra; medical image processing; CBMIR; GLCM; GP-MI; background region; content-based medical image retrieval; feature extraction; gradient phase mutual information; gray level cooccurrence matrix; masked image; rotation angle; texture feature; Computed tomography; Educational institutions; Feature extraction; Image retrieval; Medical diagnostic imaging; Mutual information; gradient phase mutual information; gray level co-occurrence matrix; masked image; medical image retrieval; texture feature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Communication and Computing (ICSPCC), 2012 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4673-2192-1
  • Type

    conf

  • DOI
    10.1109/ICSPCC.2012.6335699
  • Filename
    6335699