Dataset Open Access

# 3D Dataset "Computation of Exact g-Factor Maps in 3D GRAPPA Reconstructions"

Rabanillo, Iñaki; Zhu, Ante; Aja-Fernández, Santiago; Alberola-López, Carlos; Hernando, Diego

### Dublin Core Export

<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:creator>Rabanillo, Iñaki</dc:creator>
<dc:creator>Zhu, Ante</dc:creator>
<dc:creator>Aja-Fernández, Santiago</dc:creator>
<dc:creator>Alberola-López, Carlos</dc:creator>
<dc:creator>Hernando, Diego</dc:creator>
<dc:date>2018-06-05</dc:date>
<dc:description>Datasets used in the paper entitled "", containing the following acquisitions:

1) Simulated abdomen data set: we have synthetized a 3D volume using the simulation environment XCAT based on the extended cardio-torso phantom. We simulated a T1-weighted acquisition using the following acquisition parameters: TE/TR=1.5/3ms, flip angle=60º, acquisition matrix size=60x60x32. A 32-coil acquisition was simulated by modulating the image using artificial sensitivity maps coded for each coil. The noise-free coil images were transformed into the \bk--space and corrupted with synthetic Gaussian noise characterized by the matrices $$\Gamma_k$$and $$C_k$$ with SNR=25 for each coil, and the correlation coefficient between coils was set to $$\rho$$=0.1$. For statistical purposes, 4000 realizations of each image were used. 2) Water phantom acquisition: A MR phantom sphere with solution (GE Medical Systems, Milwaukee, WI) was scanned in a 32-channel head coil on a 3.0T scanner (MR750, GE Healthcare, Waukesha, WI). A spoiled gradient-echo acquisition with 100 realizations of the same fully-encoded k-space sampling was used. Acquisition parameters included: coronal view, TE/TR=0.96/3.69ms, flip angle=12º, field of view=22x22$x30.7$$cm³$$, acquisition matrix size=60x60x32, bandwidth=62.5KHz. We corrected for $$B_0$$ field drift related phase variations and magnitude decay by a pre-processing step. First we estimated the phase-shift between realizations from the center of the k-space as a cubic function of time and removed it afterwards. And, second, we estimated the magnitude-decay in the k-space as a linear function and substracted it in order not to affect the noise.

3) In vivo acquisition: in order to assess the feasibility of the proposed method, after obtaining the approval fo the local institutional review board (IRB), a volunteer was scanned in a 32-channel head coil on a 3.0T scanner (MR750, GE Healthcare, Waukesha, WI). A spoiled gradient-echo acquisition of a fully-encoded \bk--space sampling was used. Acquisition parameters included: coronal view, TE/TR=2.2/5.7ms, flip angle=12º,field of view=22x22x22$$cm³$$, matrix size=220x220x220, bandwidth=62.5\$KHz.</dc:description>
<dc:identifier>https://zenodo.org/record/1283312</dc:identifier>
<dc:identifier>10.5281/zenodo.1283312</dc:identifier>
<dc:identifier>oai:zenodo.org:1283312</dc:identifier>
<dc:relation>doi:10.5281/zenodo.1283311</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:subject>Phantom</dc:subject>
<dc:subject>MRI</dc:subject>
<dc:subject>Noise</dc:subject>
<dc:subject>GRAPPA</dc:subject>
<dc:subject>Parallel Imaging</dc:subject>
<dc:title>3D Dataset "Computation of Exact g-Factor Maps in 3D GRAPPA Reconstructions"</dc:title>
<dc:type>info:eu-repo/semantics/other</dc:type>
<dc:type>dataset</dc:type>
</oai_dc:dc>

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