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Signal processing algorithms for removing banding artifacts in MRI

Björk, Marcus; Gudmundson, Erik LU ; Barral, Joëlle K. and Stoica, Petre (2011) 19th European Signal Processing Conference, EUSIPCO 2011 In European Signal Processing Conference p.1000-1004
Abstract
In magnetic resonance imaging (MRI), the balanced steadystate

free precession (bSSFP) pulse sequence has shown to

be of great interest, due to its relatively high signal-to-noise

ratio in a short scan time. However, images acquired with

this pulse sequence suffer from banding artifacts due to offresonance

effects. These artifacts typically appear as black

bands covering parts of the image and they severely degrade

the image quality. In this paper, we present a fast two-step

algorithm for estimating the unknowns in the signal model

and removing the banding artifacts. The first step consists

of rewriting the model in such a way that it becomes... (More)
In magnetic resonance imaging (MRI), the balanced steadystate

free precession (bSSFP) pulse sequence has shown to

be of great interest, due to its relatively high signal-to-noise

ratio in a short scan time. However, images acquired with

this pulse sequence suffer from banding artifacts due to offresonance

effects. These artifacts typically appear as black

bands covering parts of the image and they severely degrade

the image quality. In this paper, we present a fast two-step

algorithm for estimating the unknowns in the signal model

and removing the banding artifacts. The first step consists

of rewriting the model in such a way that it becomes linear

in the unknowns (this step is named Linearization for Off-

Resonance Estimation, or LORE). In the second step, we use

a Gauss-Newton iterative optimization with the parameters

obtained by LORE as initial guesses. We name the full algorithm

LORE-GN. Using both simulated and in vivo data,

we show the performance gain associated with using LOREGN

as compared to general methods commonly employed in

similar cases. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
European Signal Processing Conference
pages
5 pages
publisher
European Association for Signal Processing (EURASIP)
conference name
19th European Signal Processing Conference, EUSIPCO 2011
external identifiers
  • scopus:84863740966
ISSN
2219-5491
language
English
LU publication?
yes
id
28216185-e6a5-4376-a97f-46c3a46705e4 (old id 2225414)
alternative location
http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569423215.pdf
date added to LUP
2012-01-27 16:52:34
date last changed
2017-04-16 03:58:10
@inproceedings{28216185-e6a5-4376-a97f-46c3a46705e4,
  abstract     = {In magnetic resonance imaging (MRI), the balanced steadystate<br/><br>
free precession (bSSFP) pulse sequence has shown to<br/><br>
be of great interest, due to its relatively high signal-to-noise<br/><br>
ratio in a short scan time. However, images acquired with<br/><br>
this pulse sequence suffer from banding artifacts due to offresonance<br/><br>
effects. These artifacts typically appear as black<br/><br>
bands covering parts of the image and they severely degrade<br/><br>
the image quality. In this paper, we present a fast two-step<br/><br>
algorithm for estimating the unknowns in the signal model<br/><br>
and removing the banding artifacts. The first step consists<br/><br>
of rewriting the model in such a way that it becomes linear<br/><br>
in the unknowns (this step is named Linearization for Off-<br/><br>
Resonance Estimation, or LORE). In the second step, we use<br/><br>
a Gauss-Newton iterative optimization with the parameters<br/><br>
obtained by LORE as initial guesses. We name the full algorithm<br/><br>
LORE-GN. Using both simulated and in vivo data,<br/><br>
we show the performance gain associated with using LOREGN<br/><br>
as compared to general methods commonly employed in<br/><br>
similar cases.},
  author       = {Björk, Marcus and Gudmundson, Erik and Barral, Joëlle K. and Stoica, Petre},
  booktitle    = {European Signal Processing Conference},
  issn         = {2219-5491},
  language     = {eng},
  pages        = {1000--1004},
  publisher    = {European Association for Signal Processing (EURASIP)},
  title        = {Signal processing algorithms for removing banding artifacts in MRI},
  year         = {2011},
}