• DocumentCode
    1323337
  • Title

    New variants of a method of MRI scale standardization

  • Author

    Nyúl, László G. ; Udupa, Jayaram K. ; Zhang, Xuan

  • Author_Institution
    Dept. of Radiol., Pennsylvania Univ., Philadelphia, PA, USA
  • Volume
    19
  • Issue
    2
  • fYear
    2000
  • Firstpage
    143
  • Lastpage
    150
  • Abstract
    One of the major drawbacks of magnetic resonance imaging (MRI) has been the lack of a standard and quantifiable interpretation of image intensities. Unlike in other modalities, such as X-ray computerized tomography, MR images taken for the same patient on the same scanner at different times may appear different from each other due to a variety of scanner-dependent variations and, therefore, the absolute intensity values do not have a fixed meaning. The authors have devised a two-step method wherein all images (independent of patients and the specific brand of the MR scanner used) can be transformed in such a may that for the same protocol and body region, in the transformed images similar intensities will have similar tissue meaning. Standardized images can be displayed with fixed windows without the need of per-case adjustment. More importantly, extraction of quantitative information about healthy organs or about abnormalities can be considerably simplified. This paper introduces and compares new variants of this standardizing method that can help to overcome some of the problems with the original method.
  • Keywords
    biomedical MRI; medical image processing; MR scanner brand; MRI scale standardization method; abnormalities; absolute intensity values; body region; fixed meaning; healthy organs; image display; image normalization; magnetic resonance imaging; medical diagnostic imaging; quantitative information extraction; scanner-dependent variations; tissue meaning; two-step method; Body regions; Computed tomography; Data mining; Displays; Humans; Image segmentation; Magnetic resonance imaging; Protocols; Standardization; X-ray imaging; Algorithms; Brain; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Multiple Sclerosis;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.836373
  • Filename
    836373