General formulation for quantitative G-factor calculation in GRAPPA reconstructions

In this work a theoretical description for practical quantitative estimation of the noise enhancement in generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstructions, equivalent to the geometry (g)‐factor in sensitivity encoding for fast MRI (SENSE) reconstructions, is descri...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Magnetic resonance in medicine Ročník 62; číslo 3; s. 739 - 746
Hlavní autori: Breuer, Felix A., Kannengiesser, Stephan A.R., Blaimer, Martin, Seiberlich, Nicole, Jakob, Peter M., Griswold, Mark A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.09.2009
Predmet:
Algorithms
Brain - anatomy & histology
g-factor
GRAPPA
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Information Storage and Retrieval - methods
Magnetic Resonance Imaging - methods
parallel imaging
Phantoms, Imaging
quantitative noise enhancement
Reproducibility of Results
Sensitivity and Specificity
ISSN:0740-3194, 1522-2594, 1522-2594
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this work a theoretical description for practical quantitative estimation of the noise enhancement in generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstructions, equivalent to the geometry (g)‐factor in sensitivity encoding for fast MRI (SENSE) reconstructions, is described. The GRAPPA g‐factor is derived directly from the GRAPPA reconstruction weights. The procedure presented here also allows the calculation of quantitative g‐factor maps for both the uncombined and combined accelerated GRAPPA images. This enables, for example, a fast comparison between the performances of various GRAPPA reconstruction kernels or SENSE reconstructions. The applicability of this approach is validated on phantom studies and demonstrated using in vivo images for 1D and 2D parallel imaging. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
Bibliografia:ark:/67375/WNG-DKBLRMRK-2
ArticleID:MRM22066
istex:ABB1E377D3CE329449F89773591ABBF20F630096
Bavarian Ministry of Economic Affairs and Technology (BayStMWIVT)
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:0740-3194
1522-2594
1522-2594
DOI:10.1002/mrm.22066