ArticleMagnetic resonance in medicine2016
Diffusion in realistic biophysical systems can lead to aliasing effects in diffusion spectrum imaging.
Article in Magnetic resonance in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Research Progress in Diffusion Spectrum Imaging.Brain sciences · 2023Review
- High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation.NeuroImage · 2021Article
- Comparison of q-Space Reconstruction Methods for Undersampled Diffusion Spectrum Imaging Data.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2020Article
- Modelling white matter with spherical deconvolution: How and why?NMR in biomedicine · 2019Review
- Accelerated radial diffusion spectrum imaging using a multi-echo stimulated echo diffusion sequence.Magnetic resonance in medicine · 2018Article
- A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment design.NeuroImage · 2017Article
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Authors and funding
6 authors.
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Abstract
purposeDiffusion spectrum imaging (DSI) is an imaging technique that has been successfully applied to resolve white matter crossings in the human brain. However, its accuracy in complex microstructure environments has not been well characterized. THEORY AND
methodsHere we have simulated different tissue configurations, sampling schemes, and processing steps to evaluate DSI performances' under realistic biophysical conditions. A novel approach to compute the orientation distribution function (ODF) has also been developed to include biophysical constraints, namely integration ranges compatible with axial fiber diffusivities.
resultsPerformed simulations identified several DSI configurations that consistently show aliasing artifacts caused by fast diffusion components for both isotropic diffusion and fiber configurations. The proposed method for ODF computation showed some improvement in reducing such artifacts and improving the ability to resolve crossings, while keeping the quantitative nature of the ODF.
conclusionIn this study, we identified an important limitation of current DSI implementations, specifically the presence of aliasing due to fast diffusion components like those from pathological tissues, which are not well characterized, and can lead to artifactual fiber reconstructions. To minimize this issue, a new way of computing the ODF was introduced, which removes most of these artifacts and offers improved angular resolution. Magn Reson Med 76:1837-1847, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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