17 research outputs found

    Impact of MR Acquisition Parameters on DTI Scalar Indexes: A Tractography Based Approach

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    <div><p>Acquisition parameters play a crucial role in Diffusion Tensor Imaging (DTI), as they have a major impact on the values of scalar measures such as Fractional Anisotropy (FA) or Mean Diffusivity (MD) that are usually the focus of clinical studies based on white matter analysis. This paper presents an analysis on the impact of the variation of several acquisition parameters on these scalar measures with a novel double focus. First, a tractography-based approach is employed, motivated by the significant number of clinical studies that are carried out using this technique. Second, the consequences of simultaneous changes in multiple parameters are analyzed: number of gradient directions, b-value and voxel resolution. Results indicate that the FA is most affected by changes in the number of gradients and voxel resolution, while MD is specially influenced by variations in the b-value. Even if the choice of a tractography algorithm has an effect on the numerical values of the final scalar measures, the evolution of these measures when acquisition parameters are modified is parallel.</p></div

    2-D boxplot of Total Volume, VB, (<i>mm</i><sup>3</sup>) versus OV (percentage) for RKT (red) and GT (blue) on CCA and CGL fiber bundles at <i>B</i> = 800 <i>s</i>/<i>mm</i><sup>2</sup>, and different configurations of <i>R</i> and <i>G</i>.

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    <p>The limits of each rectangle indicate the first and third quartile values for both boxplots. Dotted lines denote median values of each boxplot, while solid and dashed lines gather reconstructions that share the same voxel resolution.</p

    Average values for RKT(red) and GT(blue) on CCA(left column) and CGL (right column) for FA, MD, AD and RD.

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    <p>Central lines represent median values; upper and lower lines of the shaded areas represent the first and third quartile of the data. Dashed lines between groups represent average values of each group.</p

    RKT (left) and GT (right) reconstructions of one side of the brain (CC, red and orange; CG, green) for <i>G</i> = 61 gradients, <i>R</i> = 2 × 2 × 2 <i>mm</i><sup>3</sup>, <i>b</i> = 1000 <i>s</i>/<i>mm</i><sup>2</sup>.

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    <p>RKT (left) and GT (right) reconstructions of one side of the brain (CC, red and orange; CG, green) for <i>G</i> = 61 gradients, <i>R</i> = 2 × 2 × 2 <i>mm</i><sup>3</sup>, <i>b</i> = 1000 <i>s</i>/<i>mm</i><sup>2</sup>.</p

    Main peaks from the fiber ODFs estimated in the “HARDI Reconstruction Challenge 2013” phantom.

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    <p>Visualization of the main peaks extracted from the fiber ODFs reconstructed from the SMF-based data generated with SNR = 20 in a complex region of the “HARDI Reconstruction Challenge 2013” phantom. Results are based on reconstructions using 400 iterations. Peaks are visualized as thin cylinders.</p

    Reconstruction accuracy of RUMBA-SD and dRL-SD measured in phantoms with different volume fractions.

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    <p>Reconstruction accuracy of RUMBA-SD (blue color) and dRL-SD (red color) is shown in terms of the volume fraction of the smaller fiber bundle (upper panel) and the success rate (middle panel) in the 41 synthetic phantoms with inter-fiber angle equal to 70 degrees, using different volume fractions. The lower panel shows results similar to those depicted in the upper panel but considering only voxels where the two fiber bundles were detected. The discontinuous diagonal black line in the upper and lower panels represents the ideal result as a reference. The continuous coloured lines in each plot denote the mean values for each method. The semi-transparent coloured bands represent the values within one standard deviation to both sides of the mean. Results refer to the datasets with SNR = 15 and dictionary created with the true diffusivities.</p
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