An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization

Chen, Li; Weng, Zhiqiang; Goh, Lai Yoong; Garland, Marc

doi:10.1016/s1090-7807(02)00069-1

Cited by 115 publications

(101 citation statements)

References 16 publications

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“…The time-domain signals were converted to high-resolution spectra through Fourier transformation, automatic phase correction, 43 and baseline correction using in-house Matlab scripts based on matNMR. 44 The AOT resonance lines were sufficiently narrow to be detectable with the triple-stimulated sequence for both the cubic and reverse hexagonal samples.…”

Section: Methodsmentioning

confidence: 99%

NMR diffusion-encoding with axial symmetry and variable anisotropy: Distinguishing between prolate and oblate microscopic diffusion tensors with unknown orientation distribution

Eriksson

Lasič

Nilsson

et al. 2015

The Journal of Chemical Physics

173

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We introduce a nuclear magnetic resonance method for quantifying the shape of axially symmetric microscopic diffusion tensors in terms of a new diffusion anisotropy metric, DΔ, which has unique values for oblate, spherical, and prolate tensor shapes. The pulse sequence includes a series of equal-amplitude magnetic field gradient pulse pairs, the directions of which are tailored to give an axially symmetric diffusion-encoding tensor b with variable anisotropy bΔ. Averaging of data acquired for a range of orientations of the symmetry axis of the tensor b renders the method insensitive to the orientation distribution function of the microscopic diffusion tensors. Proof-of-principle experiments are performed on water in polydomain lyotropic liquid crystals with geometries that give rise to microscopic diffusion tensors with oblate, spherical, and prolate shapes. The method could be useful for characterizing the geometry of fluid-filled compartments in porous solids, soft matter, and biological tissues.

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Section: Methodsmentioning

confidence: 99%

NMR diffusion-encoding with axial symmetry and variable anisotropy: Distinguishing between prolate and oblate microscopic diffusion tensors with unknown orientation distribution

Eriksson

Lasič

Nilsson

et al. 2015

The Journal of Chemical Physics

173

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“…The spectra were then phase corrected including zeroand first-order correction terms by using an automated algorithm based on minimizing entropy. 21 The spectra were then shifted in frequency to place the peak for NAA at 2.04 ppm, normalized by their L2 norm, and subjected to Hankel-Lanczos singular value decomposition 22 for the removal of residual spectral content arising from water. Spectral components were then quantified automatically by using the freeware SPID (http://homes.esat.…”

Section: Cssmrs Implementation and Spectral Analysismentioning

confidence: 99%

Constrained Source Space MR Spectroscopy: Multiple Voxels, No Gradient Readout

Landheer¹,

Sahgal²,

Das³

et al. 2015

AJNR Am J Neuroradiol

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“…In previous articles, different functions have been proposed for the automatic phase correction of 1D spectra, including maximizing the lowest point of the spectrum [7] or the entropy of the spectrum. [18] In this work, we introduce a new objective function, designed specifically for 2D spectra, which we call whitening and which is defined as the maximization of the number of white pixels in a 2D image. A 2D NMR spectrum can be considered as a computer image formed by pixels.…”

Section: Discussionmentioning

confidence: 99%

Automatic phase correction of 2D NMR spectra by a whitening method

Balacco¹,

Cobas²

2009

Magnetic Reson in Chemistry

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A new method for the automatic phase correction of multidimensional NMR spectra is described. It is based on the whitening concept formulated as the 'maximization of the number of white pixels into a bitmap that corresponds to the spectrum'. This process of maximization can be factorized along the individual axes of the spectrum and this property makes the method robust and fast. It employs a statistic measure based on a large number of spectral data points and, for this reason, is very tolerant to low signal-to-noise ratio (SNR) and local artifacts. The algorithm can efficiently phase either homonuclear or heteronuclear experiments and, unlike other previous methods, it can also process automatically spectra containing positive or negative peaks so that it is not necessary to deal with individual or special cases

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An efficient algorithm for automatic phase correction of NMR spectra based on entropy minimization

Cited by 115 publications

References 16 publications

NMR diffusion-encoding with axial symmetry and variable anisotropy: Distinguishing between prolate and oblate microscopic diffusion tensors with unknown orientation distribution

NMR diffusion-encoding with axial symmetry and variable anisotropy: Distinguishing between prolate and oblate microscopic diffusion tensors with unknown orientation distribution

Constrained Source Space MR Spectroscopy: Multiple Voxels, No Gradient Readout

Automatic phase correction of 2D NMR spectra by a whitening method

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