TY - JOUR

T1 - Automatic phasing of MR images. Part II

T2 - Voxel-wise phase estimation

AU - Larry Bretthorst, G.

PY - 2008/4/1

Y1 - 2008/4/1

N2 - 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.

AB - 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.

KW - Absorption-mode images

KW - Bayesian probability theory

KW - Zero-order phase estimation

UR - http://www.scopus.com/inward/record.url?scp=40949146127&partnerID=8YFLogxK

U2 - 10.1016/j.jmr.2007.12.011

DO - 10.1016/j.jmr.2007.12.011

M3 - Article

C2 - 18187351

AN - SCOPUS:40949146127

VL - 191

SP - 193

EP - 201

JO - Journal of Magnetic Resonance

JF - Journal of Magnetic Resonance

SN - 1090-7807

IS - 2

ER -