• DocumentCode
    3249402
  • Title

    Liver CT image retrieval based on non-tensor product wavelet

  • Author

    Yu, Mei ; Lu, Zhentai ; Feng, Qianjin ; Chen, Wufan

  • Author_Institution
    Sch. of Biomed. Eng., Southern Med. Univ., Guangzhou, China
  • fYear
    2010
  • fDate
    10-13 June 2010
  • Firstpage
    67
  • Lastpage
    70
  • Abstract
    This paper presents a content-based medical image retrieval (CBIR) method that used in medical CT images of liver lesions with a computer-assisted diagnosis. According to medical CT images characteristics of blurred boundaries and the unconspicuous region, the liver region of interest is extracted by using semi-automatic method. We extract local co-occurrence matrix texture features and intensity features, and use improved non-tensor product wavelet filter to extract the image global features. Experimental results show that this method can improve the detection rate of lesions. It obtains good results in hepatic hemangioma and HCC which are difficult differential diagnosis both of rich blood supply to tumors.
  • Keywords
    cancer; computerised tomography; content-based retrieval; feature extraction; filtering theory; image retrieval; image texture; liver; medical image processing; tumours; wavelet transforms; computer-assisted diagnosis; content-based medical image retrieval method; hepatic hemangioma; image global feature extraction; liver lesions; local co-occurrence matrix intensity feature extraction; local co-occurrence matrix texture feature extraction; medical CT imaging; nontensor product wavelet filter; semi-automatic method; tumors; Biomedical imaging; Blood; Computed tomography; Computer aided diagnosis; Content based retrieval; Filters; Image retrieval; Lesions; Liver; Medical diagnostic imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Medical Image Analysis and Clinical Applications (MIACA), 2010 International Conference on
  • Conference_Location
    Guangdong
  • Print_ISBN
    978-1-4244-8011-1
  • Type

    conf

  • DOI
    10.1109/MIACA.2010.5528419
  • Filename
    5528419