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


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    <subfield code="a">The authors acknowledge MICIN for grants TEC2013-44194P, TEC 2014-57428 and TEC2017-82408-R, as well as Junta de Castilla y León for grant VA069U16. The first author acknowledges MINECO for FPI grant BES-2014-069524.</subfield>
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    <subfield code="u">University of Wisconsin-Madison</subfield>
    <subfield code="a">Zhu, Ante</subfield>
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    <subfield code="u">Universidad de Valladolid</subfield>
    <subfield code="a">Aja-Fernández, Santiago</subfield>
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    <subfield code="u">Universidad de VAlladolid</subfield>
    <subfield code="a">Alberola-López, Carlos</subfield>
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    <subfield code="u">University of Wisconsin-Madison</subfield>
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    <subfield code="a">Rabanillo, Iñaki</subfield>
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    <subfield code="a">3D Dataset "Computation of Exact g-Factor Maps in 3D GRAPPA Reconstructions"</subfield>
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    <subfield code="a">&lt;p&gt;Datasets used in the paper entitled &amp;quot;&amp;quot;, containing the following acquisitions:&lt;/p&gt;

&lt;p&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;strong&gt;1) Simulated abdomen data set&lt;/strong&gt;: 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=60&amp;ordm;, 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 &lt;span class="math-tex"&gt;\(\Gamma_k\)&lt;/span&gt;and&amp;nbsp;&lt;span class="math-tex"&gt;\(C_k\)&lt;/span&gt; with SNR=25 for each coil, and the correlation coefficient between coils was set to &lt;span class="math-tex"&gt;\(\rho\)&lt;/span&gt;=0.1$. For statistical purposes, 4000 realizations of each image were used.&lt;/p&gt;

&lt;p&gt;&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;strong&gt;2) Water phantom acquisition&lt;/strong&gt;: 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=12&amp;ordm;, field of view=22x22$x30.7&lt;span class="math-tex"&gt;\(cm³\)&lt;/span&gt;, acquisition matrix size=60x60x32, bandwidth=62.5KHz. We corrected for &lt;span class="math-tex"&gt;\(B_0\)&lt;/span&gt; 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.&lt;/p&gt;

&lt;p&gt;&lt;br&gt;
&amp;nbsp;&amp;nbsp;&amp;nbsp; &lt;strong&gt;3) In vivo acquisition&lt;/strong&gt;: 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=12&amp;ordm;,field of view=22x22x22&lt;span class="math-tex"&gt;\(cm³\)&lt;/span&gt;, matrix size=220x220x220, bandwidth=62.5$KHz.&lt;/p&gt;</subfield>
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