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Titolo:
ON THE USE OF BAYESIAN PROBABILITY-THEORY FOR ANALYSIS OF EXPONENTIALDECAY DATA - AN EXAMPLE TAKEN FROM INTRAVOXEL INCOHERENT MOTION EXPERIMENTS
Autore:
NEIL JJ; BRETTHORST GL;
Indirizzi:
ST LOUIS CHILDRENS HOSP,DEPT PEDIAT,DIV NEUROL,CAMPUS BOX 8116,400 S KINGSHIGHWAY ST LOUIS MO 63110 WASHINGTON UNIV,SCH MED,DEPT PEDIAT,DIV PEDIAT NEUROL ST LOUIS MO 63110 WASHINGTON UNIV,DEPT CHEM ST LOUIS MO 63130
Titolo Testata:
Magnetic resonance in medicine
fascicolo: 5, volume: 29, anno: 1993,
pagine: 642 - 647
SICI:
0740-3194(1993)29:5<642:OTUOBP>2.0.ZU;2-L
Fonte:
ISI
Lingua:
ENG
Soggetto:
PARAMETER-ESTIMATION; SIGNAL-DETECTION; MODEL SELECTION; DIFFUSION;
Keywords:
BAYESIAN PROBABILITY THEORY; NONLINEAR LEAST SQUARES; INTRAVOXEL INCOHERENT MOTION;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
19
Recensione:
Indirizzi per estratti:
Citazione:
J.J. Neil e G.L. Bretthorst, "ON THE USE OF BAYESIAN PROBABILITY-THEORY FOR ANALYSIS OF EXPONENTIALDECAY DATA - AN EXAMPLE TAKEN FROM INTRAVOXEL INCOHERENT MOTION EXPERIMENTS", Magnetic resonance in medicine, 29(5), 1993, pp. 642-647

Abstract

Traditionally, the method of nonlinear least squares (NLLS) analysis has been used to estimate the parameters obtained from exponential decay data. In this study, we evaluated the use of Bayesian probability theory to analyze such data; specifically, that resulting from intravoxel incoherent motion NMR experiments. Analysis was done both on simulated data to which different amounts of Gaussian noise had been added and on actual data derived from rat brain. On simulated data, Bayesian analysis performed substantially better than NLLS under conditions of relatively low signal-to-noise ratio. Bayesian probability theory alsooffers the advantages of: a) not requiring initial parameter estimates and hence not being susceptible to errors due to incorrect starting values and b) providing a much better representation of the uncertainty in the parameter estimates in the form of the probability density function. Bayesian analysis of rat brain data was used to demonstrate the shape of the probability density function from data sets of different quality.

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Documento generato il 22/09/20 alle ore 06:39:24