Signal processing algorithms for removing banding artifacts in MRI
(2011) 19th European Signal Processing Conference, EUSIPCO 2011 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:
https://lup.lub.lu.se/record/2225414
- author
- Björk, Marcus ; Gudmundson, Erik LU ; Barral, Joëlle K. and Stoica, Petre
- organization
- publishing date
- 2011
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- European Signal Processing Conference
- pages
- 5 pages
- publisher
- European Association for Signal Processing (EURASIP)
- conference name
- 19th European Signal Processing Conference, EUSIPCO 2011
- conference location
- Barcelona, Spain
- conference dates
- 2011-08-29 - 2011-09-02
- external identifiers
-
- scopus:84863740966
- ISSN
- 2219-5491
- language
- English
- LU publication?
- yes
- additional info
- Received Best Student Paper Award.
- 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
- 2016-04-01 14:30:30
- date last changed
- 2022-01-28 00:57:26
@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}},
url = {{http://www.eurasip.org/Proceedings/Eusipco/Eusipco2011/papers/1569423215.pdf}},
year = {{2011}},
}