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• W2135860438 abstract "Diffusion tensor imaging (DTI) is achieved by collecting a series of diffusion-weighted images (DWIs). Signal averaging of multiple repetitions can be performed in the k-space (k-avg) or in the image space (m-avg) to improve the image quality. Alternatively, one can treat each acquisition as an independent image and use all of the data to reconstruct the DTI without doing any signal averaging (no-avg). To compare these three approaches, in this study, in vivo DTI data were collected from five normal mice. Noisy data with signal-to-noise ratios (SNR) that varied between five and 30 (before averaging) were then simulated. The DTI indices, including relative anisotropy (RA), trace of diffusion tensor (TR), axial diffusivity (λ║), and radial diffusivity (λ⊥), derived from the k-avg, m-avg, and no-avg, were then compared in the corpus callosum white matter, cortex gray matter, and the ventricles. We found that k-avg and m-avg enhanced the SNR of DWI with no significant differences. However, k-avg produced lower RA in the white matter and higher RA in the gray matter, compared to the m-avg and no-avg, regardless of SNR. The latter two produced similar DTI quantifications. We concluded that k-avg is less preferred for DTI brain imaging." @default.
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• W2135860438 date "2013-11-01" @default.
• W2135860438 modified "2023-09-24" @default.
• W2135860438 title "Comparison of mouse brain DTI maps using K-space average, image-space average, or no average approach" @default.
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• W2135860438 doi "https://doi.org/10.1016/j.mri.2013.07.015" @default.
• W2135860438 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3904870" @default.
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