• DocumentCode
    1844422
  • Title

    Automated Analysis of 1H Magnetic Resonance Metabolic Imaging Data as an Aid to Clinical Decision-Making in the Evaluation of Intracranial Lesions

  • Author

    Shungu, D.C. ; Du, S. ; Xiangling Mao ; Heier, L.A. ; Pannullo, S.C. ; Sajda, P.

  • Author_Institution
    Cornell Univ., New York
  • fYear
    2007
  • fDate
    22-26 Aug. 2007
  • Firstpage
    4327
  • Lastpage
    4330
  • Abstract
    Proton magnetic resonance spectroscopic imaging ( 1H MRSI) is a noninvasive metabolic imaging technique that has emerged as a potentially powerful tool for complementing structural magnetic resonance imaging (MRI) in the clinical evaluation of neurological disorders and diagnostic decision making. However, the relative complexity of methods that are currently available for analyzing the derived multi-dimensional metabolic imaging data has slowed incorporation of the technique into routine clinical practice. This paper discusses this impediment to widespread clinical use of 1H MRSI and then describes an automated data analysis approach that promises to facilitate use of the technique in the evaluation of intracranial lesions, with the potential to enhance the specificity of MRI and improve clinical decision-making.
  • Keywords
    biomedical MRI; medical signal processing; neurophysiology; patient diagnosis; 1H MRSI data automated analysis; automated data analysis; clinical decision making; diagnostic decision making; intracranial lesion evaluation; magnetic resonance metabolic imaging; neurological disorder clinical evaluation; noninvasive metabolic imaging technique; proton magnetic resonance spectroscopic imaging; Data analysis; Decision making; Image analysis; Impedance; Lesions; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Protons; Spectroscopy; Brain; Brain Neoplasms; Diagnosis, Differential; Humans; Magnetic Resonance Imaging; Protons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
  • Conference_Location
    Lyon
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-0787-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2007.4353294
  • Filename
    4353294