• DocumentCode
    1849874
  • Title

    Medical Image Retrieval Based on Fractal Dimension

  • Author

    Wu, Jianhua ; Jiang, Chunhua ; Yao, Liqiang

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Boston, MA
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    2959
  • Lastpage
    2961
  • Abstract
    Content-based medical image retrieval becomes a hot research topic due to the rapid increase of image database. It is useful that a doctor consults analogical cases to diagnose for a patient. So it is very important for doctors to quickly and exactly search out the similar pathological images from large numbers of images in clinic. Fractal texture feature is introduced to medical images, according to experiments, it is discovered that the normal lung and several kinds of common lung diseases CT images have different fractal dimensions, which indicates that fractal dimensions of images can distinguish most lung diseases. Fractal feature is applied in medical images retrieval, and compared with general approaches, experiments show that high precision and recall of retrieval are achieved, and our method also can achieve a comparatively lower computation cost, and the retrieval time is short. The method is applied well and gives much better performance in medical images retrieval.
  • Keywords
    feature extraction; fractals; image retrieval; medical image processing; feature extraction; fractal dimension; fractal texture feature; medical image retrieval; pathological images; Biomedical imaging; Content based retrieval; Diseases; Fractals; Image databases; Image retrieval; Information retrieval; Lungs; Medical diagnostic imaging; Pathology; Medical images retrieval; texture feature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.268
  • Filename
    4709454