• DocumentCode
    2739993
  • Title

    An Enhancement Method for Small Brain Metastases in T1w MRI

  • Author

    Liu Xing-Sheng ; Nie Sheng-dong ; Sun Xi-wen

  • Author_Institution
    Sch. of Med. Instrum. & Food Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    416
  • Lastpage
    419
  • Abstract
    Brain metastases are becoming an increasingly important cause of mortality among metastatic cancers, which accounts for over half of brain tumors. Early detection of brain metastases could have a significant impact on treatment outcomes and therefore essentially circumvent the spread of such tumors. In this work, a computerized image enhancement algorithm has been exploited to the benefit of improving detection of brain metastases. The algorithm first applied a clustering algorithm over each image pixel and then carried out the histogram normalization according to the parameters achieved by the clustering algorithm. Experimental results demonstrated that the contrast between BM and surrounding tissues was enhanced significantly by the proposed algorithm.
  • Keywords
    biomedical MRI; brain; cancer; image enhancement; medical image processing; tumours; T1w MRI; brain tumors; clustering algorithm; computerized image enhancement; histogram normalization; metastatic cancers; mortality; patient treatment; small brain metastases; Biomedical imaging; Cancer; Clustering algorithms; Gray-scale; High-resolution imaging; Histograms; Lesions; Magnetic resonance imaging; Metastasis; Neoplasms; MRI; brain metastases; nonlinear transformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-0-7695-3735-1
  • Type

    conf

  • DOI
    10.1109/FSKD.2009.256
  • Filename
    5358554