Literature DB >> 18187351

Automatic phasing of MR images. Part II: voxel-wise phase estimation.

G Larry Bretthorst1.   

Abstract

Magnetic resonance images are typically displayed as the absolute value of the discrete Fourier transform of the k-space data. However, absorption-mode images, the real part of the discrete Fourier transform of the data after applying an appropriate phase correction, have significant advantages over absolute-value images. In a companion paper, the problem of estimating the phase parameters needed to produce an absorption-mode image when the phase of the complex image varies linearly as a function of position, a situation common in magnetic resonance images, was addressed. However, some magnetic resonance images have phases that can vary in a complicated, nonlinear, positionally dependent fashion. To produce an absorption-mode image from these data, one must first estimate the positionally dependent phase, and then use that phase estimate to produce an absorption-mode image. This paper addresses both of these problems by first using Bayesian probability theory to estimate the constant or zero-order phase as a function of image position, and then the calculations are illustrated by using them to generate absorption-mode images from data where the phase of the image is a nonlinear function of position.

Mesh:

Year:  2007        PMID: 18187351     DOI: 10.1016/j.jmr.2007.12.011

Source DB:  PubMed          Journal:  J Magn Reson        ISSN: 1090-7807            Impact factor:   2.229


  7 in total

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Authors:  Chuan Huang; Jean-Philippe Galons; Christian G Graff; Eric W Clarkson; Ali Bilgin; Bobby Kalb; Diego R Martin; Maria I Altbach
Journal:  Magn Reson Med       Date:  2014-04-17       Impact factor: 4.668

2.  Diffusion effects on longitudinal relaxation in poorly mixed compartments.

Authors:  J R Anderson; Q Ye; J J Neil; J J H Ackerman; J R Garbow
Journal:  J Magn Reson       Date:  2011-04-01       Impact factor: 2.229

3.  Optimal decay rate constant estimates from phased array data utilizing joint Bayesian analysis.

Authors:  James D Quirk; Alexander L Sukstanskii; G Larry Bretthorst; Dmitriy A Yablonskiy
Journal:  J Magn Reson       Date:  2009-01-13       Impact factor: 2.229

4.  Phase-aligned multiple spin-echo averaging: a simple way to improve signal-to-noise ratio of in vivo mouse spinal cord diffusion tensor image.

Authors:  Tsang-Wei Tu; Matthew D Budde; Mingqiang Xie; Ying-Jr Chen; Qing Wang; James D Quirk; Sheng-Kwei Song
Journal:  Magn Reson Imaging       Date:  2014-08-01       Impact factor: 2.546

5.  A signal transformational framework for breaking the noise floor and its applications in MRI.

Authors:  Cheng Guan Koay; Evren Ozarslan; Peter J Basser
Journal:  J Magn Reson       Date:  2008-12-06       Impact factor: 2.229

6.  Neurological consequences of diabetic ketoacidosis at initial presentation of type 1 diabetes in a prospective cohort study of children.

Authors:  Fergus J Cameron; Shannon E Scratch; Caroline Nadebaum; Elisabeth A Northam; Ildiko Koves; Juliet Jennings; Kristina Finney; Jeffrey J Neil; R Mark Wellard; Mark Mackay; Terrie E Inder
Journal:  Diabetes Care       Date:  2014-06       Impact factor: 19.112

7.  Adaptive phase correction of diffusion-weighted images.

Authors:  Marco Pizzolato; Guillaume Gilbert; Jean-Philippe Thiran; Maxime Descoteaux; Rachid Deriche
Journal:  Neuroimage       Date:  2019-10-17       Impact factor: 6.556

  7 in total

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