Simple MATLAB and Python scripts for multi‐exponential analysis

Multi‐exponential decay is prevalent in magnetic resonance spectroscopy, relaxation, and imaging. This paper describes simple MATLAB and Python functions and scripts for regularized multi‐exponential analysis methods for 1D and 2D data and example test problems and experiments. Regularized least‐squ...

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Veröffentlicht in:Magnetic resonance in chemistry Jg. 62; H. 10; S. 698 - 711
Hauptverfasser: Afrough, Armin, Mokhtari, Rasoul, Feilberg, Karen L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Wiley Subscription Services, Inc 01.10.2024
Schlagworte:
Chalk
Crude oil
Decay
exponential decay
inverse problems
Inversions
Magnetic induction
magnetic resonance relaxation
Magnetic resonance spectroscopy
Matlab
Mixtures
multi‐exponential analysis
NMR
Porous materials
Scripts
Software
Two dimensional analysis
NMR
magnetic resonance relaxation
exponential decay
multi‐exponential analysis
1H
inverse problems
ISSN:0749-1581, 1097-458X, 1097-458X
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Zusammenfassung:Multi‐exponential decay is prevalent in magnetic resonance spectroscopy, relaxation, and imaging. This paper describes simple MATLAB and Python functions and scripts for regularized multi‐exponential analysis methods for 1D and 2D data and example test problems and experiments. Regularized least‐squares solutions provide production‐quality outputs with robust stopping rules in ~5 and ~20 lines of code for 1D and 2D inversions, respectively. The software provides an open‐architecture simple solution for transforming exponential decay data to the distribution of their decay lifetimes. Examples from magnetic resonance relaxation of a complex fluid, a Danish North Sea crude oil, and fluid mixtures in porous materials—brine/crude oil mixture in North Sea reservoir chalk—are presented. Developed codes may be incorporated in other software or directly used by other researchers, in magnetic resonance relaxation, diffusion, and imaging or other physical phenomena that require multi‐exponential analysis. Multi‐exponential decay is prevalent in magnetic resonance spectroscopy, relaxation, and imaging. This paper describes simple MATLAB and Python functions and scripts for regularized multi‐exponential analysis methods for 1D and 2D data and example test problems and experiments. Regularized least‐squares solutions provide production‐quality outputs with robust stopping rules in ~5 and ~20 lines of code for 1D and 2D inversions, respectively. The software provides an open‐architecture simple solution for transforming exponential decay data to the distribution of their decay lifetimes.
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ISSN:0749-1581
1097-458X
1097-458X
DOI:10.1002/mrc.5453