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Rapid and effective correction of RF inhomogeneity for high field magnetic resonance imaging

Cohen, Mark S. ; DuBois, Richard M. ; Zeineh, Michael M.

Human brain mapping, 2000-08, Vol.10 (4), p.204-211 [Periódico revisado por pares]

New York: John Wiley & Sons, Inc

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  • Título:
    Rapid and effective correction of RF inhomogeneity for high field magnetic resonance imaging
  • Autor: Cohen, Mark S. ; DuBois, Richard M. ; Zeineh, Michael M.
  • Assuntos: Algorithms ; Biological and medical sciences ; Brain - anatomy & histology ; human brain/anatomy and histology ; Humans ; Investigative techniques, diagnostic techniques (general aspects) ; magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Medical sciences ; Nervous system ; radio frequency ; Radio Waves ; Radiodiagnosis. Nmr imagery. Nmr spectrometry ; segmentation ; theoretical models
  • É parte de: Human brain mapping, 2000-08, Vol.10 (4), p.204-211
  • Notas: Jennifer Jones-Simon Foundation
    Tamkin Foundation
    NorthStar Fund
    Brain Mapping Medical Research Foundation
    Pierson-Lovelace Foundation
    ArticleID:HBM60
    istex:E4D2744BD53409F46C9AB0F8E474994C132178F5
    National Institute for Drug Abuse - No. R01 DA13054-01
    The Ahmanson Foundation
    ark:/67375/WNG-QCWNTLLW-B
    ObjectType-Article-2
    SourceType-Scholarly Journals-1
    ObjectType-Feature-1
    content type line 23
    ObjectType-Article-1
    ObjectType-Feature-2
  • Descrição: The well‐known variability in the distribution of high frequency electromagnetic fields in the human body causes problems in the analysis of structural information in high field magnetic resonance images. We describe a method of compensating for the purely intensity‐based effects. In our simple and rapid correction algorithm, we first use statistical means to determine the background image noise level and the edges of the image features. We next populate all “noise” pixels with the mean signal intensity of the image features. These data are then smoothed by convolution with a gaussian filter using Fourier methods. Finally, the original data that are above the noise level are normalized to the smoothed images, thereby eliminating the lowest spatial frequencies in the final, corrected data. Processing of a 124 slice, 256 × 256 volume dataset requires under 70 sec on a laptop personal computer. Overall, the method is less prone to artifacts from edges or from sensitivity to absolute head position than are other correction techniques. Following intensity correction, the images demonstrated obvious qualitative improvement and, when subjected to automated segmentation tools, the accuracy of segmentation improved, in one example, from 35.3% to 84.7% correct, as compared to a manually‐constructed gold standard. Hum. Brain Mapping 10:204–211, 2000. © 2000 Wiley‐Liss, Inc.
  • Editor: New York: John Wiley & Sons, Inc
  • Idioma: Inglês
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