• DocumentCode
    1144293
  • Title

    Multispectral analysis of the brain using magnetic resonance imaging

  • Author

    Taxt, Torfinn ; Lundervold, Arvid

  • Author_Institution
    Section for Med. Image Anal. & Pattern Anal., Bergen Univ., Norway
  • Volume
    13
  • Issue
    3
  • fYear
    1994
  • fDate
    9/1/1994 12:00:00 AM
  • Firstpage
    470
  • Lastpage
    481
  • Abstract
    The authors demonstrate an improved differentiation of the most common tissue types in the human brain and surrounding structures by quantitative validation using multispectral analysis of magnetic resonance images. This is made possible by a combination of a special training technique and an increase in the number of magnetic resonance channel images with different pulse acquisition parameters. The authors give a description of the tissue-specific multivariate statistical distributions of the pixel intensity values and discuss how their properties may be explored to improve the statistical modeling further. A statistical method to estimate the tissue-specific longitudinal and transverse relaxation times is also given. It is concluded that multispectral analysis of magnetic resonance images is a valuable tool to recognize the most common normal tissue types in the brain and surrounding structures
  • Keywords
    biomedical NMR; brain; medical image processing; spectral analysis; brain multispectral analysis; magnetic resonance channel images; medical diagnostic imaging; medical magnetic resonance imaging; pixel intensity; pulse acquisition parameters; statistical method; tissue types differentiation; tissue types recognition; tissue-specific longitudinal relaxation time; transverse relaxation time; Biomedical imaging; Humans; Image analysis; Image recognition; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Pathology; Statistical analysis; Statistical distributions;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.310878
  • Filename
    310878