Lower Error Bounds for the Estimation of Relaxation Parameters

  • A. R. Brenner
  • E. A. Penner
  • R. Gebhardt
  • W. Ameling
Conference paper

Abstract

Magnetic resonance imaging is becoming a well-established diagnostic method which is especially used to analyze and differentiate biological tissue. The quantitative characterization of tissues is achieved by using spin density and the relaxation times T1 and T2 spanning an appropriate parameter space. Regions within this space represent particular tissue types. It turns out, however, that such clusters are not very well separated; rather they tend to be very large and overlapping. There are three different reasons for the problems encountered:
  1. 1.

    It is not improbable that biological tissue shows an intrinsic heterogeneity in respect of these parameters.

     
  2. 2.

    Comparing data from different laboratories, one can observe large variations caused by different measuring methods, field dependencies, and other systematic errors. These will hopefully be eliminated by an appropriate standardization procedure, as proposed in an EEC project (Podo 1988).

     
  3. 3.

    Statistical errors are caused by parameter estimation over noisy data, sometimes combined with errors caused by the illconditioned problem of resolving multiple relaxation times.

     

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References

  1. Podo F (1988) Tissue characterization by MRI. Magn Reson Imaging 6:173–174PubMedCrossRefGoogle Scholar
  2. Zacks S (1981) Parametric statistical inference. Pergamon, OxfordGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • A. R. Brenner
    • 1
  • E. A. Penner
  • R. Gebhardt
  • W. Ameling
  1. 1.Rogowski-Institut für Elektrotechnik der Rheinisch-Westfälischen Technischen Hoch-schule AachenAachenGermany

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