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Magnetic Resonance Image Analysis

  • Robert T. Schultz
  • Amit Chakraborty
Part of the Human Brain Function book series (HBFA)

Abstract

The great advances made in neuroimaging technology during the last decade provide an unparalleled opportunity for neuroscientists to measure gross brain structure with a high degree of precision. However, this opportunity has yet to be fully realized, largely because the development of reliable, valid, and efficient means of quantifying all the information contained within the digital display has lagged far behind the ability to acquire these images. Bigler’s review (1994) demonstrated that even though many studies have employed neuroimaging methods to investigate brain-behavior relationships, the vast majority have not employed quantitative techniques (Figure 1) but rather have relied on binary, clinical readings of pathology (present or absent) and hemisphere or quadrant analyses. While such approaches are appropriate for detecting gross structural abnormalities (e.g., infarct) and active pathological processes (e.g., tumor) responsible for frank nondevelopmental neurologic disorders, the literature in neuropsychology suggests that this approach is sorely inadequate for illuminating the neuropathology of disorders where there is likely congenital or developmental disturbance (e.g., schizophrenia, dyslexia).

Keywords

White Matter Gray Matter Pixel Intensity Radio Frequency Pulse Hydrogen Proton 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Robert T. Schultz
    • 1
  • Amit Chakraborty
    • 2
  1. 1.Child Study CenterYale UniversityNew HavenUSA
  2. 2.Department of Electrical EngineeringYale UniversityNew HavenUSA

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