Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure
Evren Özarslan,Cheng Guan Koay,Timothy M. Shepherd,Michal E. Komlosh,Michal E. Komlosh,M. Okan Irfanoglu,M. Okan Irfanoglu,Carlo Pierpaoli,Peter J. Basser +8 more
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TLDR
MAP-MRI represents a new comprehensive framework to model the three-dimensional q-space MR signal and transform it into diffusion propagators, and provides several novel, quantifiable parameters that capture previously obscured intrinsic features of nervous tissue microstructure.About:
This article is published in NeuroImage.The article was published on 2013-09-01 and is currently open access. It has received 316 citations till now. The article focuses on the topics: Diffusion Anisotropy & Diffusion MRI.read more
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Dipy, a library for the analysis of diffusion MRI data
Eleftherios Garyfallidis,Eleftherios Garyfallidis,Matthew Brett,Bagrat Amirbekian,Ariel Rokem,Stefan van der Walt,Maxime Descoteaux,Ian Nimmo-Smith +7 more
TL;DR: Dipy aims to provide transparent implementations for all the different steps of dMRI analysis with a uniform programming interface, and has implemented classical signal reconstruction techniques, such as the diffusion tensor model and deterministic fiber tractography.
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Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited
Cibu Thomas,Cibu Thomas,Frank Q. Ye,M. Okan Irfanoglu,Pooja Modi,Kadharbatcha S. Saleem,David A. Leopold,Carlo Pierpaoli +7 more
TL;DR: The results indicate that, even with high-quality data, DWI tractography alone is unlikely to provide an anatomically accurate map of the brain connectome, and suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is likely to be overcome by improvements in data acquisition and analysis alone.
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Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation
TL;DR: In this article, the authors review, systematize and discuss models of diffusion in neuronal tissue, by putting them into an overarching physical context of coarse-graining over an increasing diffusion length scale.
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Imaging brain microstructure with diffusion MRI: practicality and applications
TL;DR: The article summarizes the relevant aspects of brain microanatomy and the range of diffusion‐weighted MR measurements that provide to them and reviews the evolution of mathematical and computational models that relate the diffusion MR signal to brain tissue microstructure.
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Recognition of white matter bundles using local and global streamline-based registration and clustering.
Eleftherios Garyfallidis,Marc-Alexandre Côté,François Rheault,Jasmeen Sidhu,Janice Hau,Laurent Petit,David Fortin,Stephen Cunanne,Maxime Descoteaux +8 more
TL;DR: The purpose of the proposed method, named RecoBundles, is to segment white matter bundles and make virtual dissection easier to perform and robust and adaptive to incomplete data and bundles with missing components.
References
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Journal ArticleDOI
Generalized scalar measures for diffusion MRI using trace, variance, and entropy
TL;DR: This paper details the derivation of rotationally invariant scalar measures from higher‐rank diffusion tensors (DTs) and functions defined on a unit sphere by associating anisotropy with the amount of orientational information present in the data, regardless of the imaging technique used.
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Multiple q-shell diffusion propagator imaging☆
TL;DR: In this article, the authors presented a novel technique for analytical EAP reconstruction from multiple q-shell acquisitions based on a Laplace equation by part estimation between the diffusion signal for each shell acquisition, which simplifies greatly the Fourier integral relating diffusion signal and EAP.
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High-resolution q-space imaging in porous structures
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Relationships between diffusion tensor and q-space MRI.
TL;DR: It is shown that the displacement distribution measured by q‐space MRI in both the large displacement and the long‐wavelength limits is the same 3D Gaussian displacement distribution assumed in DT‐MRI.
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Estimation of fiber orientation and spin density distribution by diffusion deconvolution
TL;DR: The proposed deconvolution method is generally applicable to different q-space imaging methods and improves the angular resolution and also provides a quantitative index of fiber spin density to refine fiber tracking.