Accelerating multidimensional NMR and MRI experiments using iterated maps

[Display omitted] •An iterated maps algorithm is applied to sparsely-sampled time domain data.•Used to reconstruct spectra from noisy 2D NMR and 3D MRI of solids data.•High quality results achieved with sparse sampling approaching theoretical minimum.•We use the QUEST sampling schedule and discuss i...

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Vydáno v:Journal of magnetic resonance (1997) Ročník 237; s. 100 - 109
Hlavní autoři: Frey, Merideth A., Sethna, Zachary M., Manley, Gregory A., Sengupta, Suvrajit, Zilm, Kurt W., Loria, J. Patrick, Barrett, Sean E.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier Inc 01.12.2013
Témata:
Algorithms
Amino Acids - chemistry
Aminohydrolases - chemistry
Image Processing, Computer-Assisted
Iterative maps
Magnetic resonance
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Magnetic Resonance Imaging - statistics & numerical data
Magnetic Resonance Spectroscopy - methods
Magnetic Resonance Spectroscopy - statistics & numerical data
Multi-dimensional nuclear magnetic resonance
Noise
Nuclear magnetic resonance
Nuclear Magnetic Resonance, Biomolecular
Projection
Sampling
Sparse sampling
Three dimensional
Iterative maps
Magnetic resonance imaging
Sparse sampling
Multi-dimensional nuclear magnetic resonance
ISSN:1090-7807, 1096-0856, 1096-0856
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Shrnutí:[Display omitted] •An iterated maps algorithm is applied to sparsely-sampled time domain data.•Used to reconstruct spectra from noisy 2D NMR and 3D MRI of solids data.•High quality results achieved with sparse sampling approaching theoretical minimum.•We use the QUEST sampling schedule and discuss its benefits for 2D NMR data.•FFT-based method is computationally fast, simple to implement, and robust. Techniques that accelerate data acquisition without sacrificing the advantages of fast Fourier transform (FFT) reconstruction could benefit a wide variety of magnetic resonance experiments. Here we discuss an approach for reconstructing multidimensional nuclear magnetic resonance (NMR) spectra and MR images from sparsely-sampled time domain data, by way of iterated maps. This method exploits the computational speed of the FFT algorithm and is done in a deterministic way, by reformulating any a priori knowledge or constraints into projections, and then iterating. In this paper we explain the motivation behind this approach, the formulation of the specific projections, the benefits of using a ‘QUasi-Even Sampling, plus jiTter’ (QUEST) sampling schedule, and various methods for handling noise. Applying the iterated maps method to real 2D NMR and 3D MRI of solids data, we show that it is flexible and robust enough to handle large data sets with significant noise and artifacts.
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Present Address: Department of Chemistry, University of California, Irvine, Irvine, CA 92697
Both authors contributed equally to this paper.
ISSN:1090-7807
1096-0856
1096-0856
DOI:10.1016/j.jmr.2013.09.005