Automatic Magnetic Resonance Imaging,

Abstract

Magnetic resonance imaging (MRI) is currently the most sensitive modality for detecting and differentiating pathophysiologic events, Transverse relaxation times (T2) provide quantitative information useful for evaluating a number of diseases (Dumitresco et al, (1986)). In MRI the observed T2 signal is modeled by m(t) = Lambda (Sigma k j =1 Sigma j e - Alpha jt) where the reciprocal of Alpha j the corresponding expected relaxation time. We consider maximum likelihood estimation of the parameters Lambda, Sigma j, Alpha j, = 1,..., k under the assumption that the number of excited protons measured follows a Poisson distribution. A computationally simple method for selecting k, the number of exponential components in the model, is proposed.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007219

Entities

People

  • Joe E. Ensor
  • Kathy Ensor
  • Lalith Misra

Organizations

  • Rice University

Tags

DTIC Thesaurus Topics

  • Automatic
  • Computer Science
  • Engineering
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Maximum Likelihood Estimation
  • Production Engineering
  • Relaxation Time
  • Resonance
  • Statistics
  • Theoretical Computer Science
  • Transverse

Fields of Study

  • Physics

Readers

  • Analytical Mechanics
  • Medical Imaging.
  • Statistical inference.