3D structure tensor analysis of light microscopy data for validating diffusion MRI
Ahmad Raza Khan,Anda Cornea,Lindsey A. Leigland,Steven G. Kohama,Sune Nørhøj Jespersen,Christopher D. Kroenke +5 more
TLDR
3D generalization of structure tensor analysis will further improve the utility of this method for validation of d-MRI by making it a more flexible experimental technique that closer resembles the inherently 3D nature ofd-MRI measurements.About:
This article is published in NeuroImage.The article was published on 2015-05-01 and is currently open access. It has received 72 citations till now. The article focuses on the topics: Structure tensor & Tractography.read more
Citations
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Journal ArticleDOI
Wiring and Molecular Features of Prefrontal Ensembles Representing Distinct Experiences
Li Ye,Li Ye,William E. Allen,Kimberly R. Thompson,Qiyuan Tian,Brian Hsueh,Charu Ramakrishnan,Ai-Chi Wang,Joshua H. Jennings,Avishek Adhikari,Casey H. Halpern,Ilana B. Witten,Alison L. Barth,Liqun Luo,Liqun Luo,Jennifer A. McNab,Karl Deisseroth +16 more
TL;DR: For example, the authors found that positive and negative-valence experiences in prefrontal cortex are represented by cell populations that differ in their causal impact on behavior, long-range wiring and gene expression profiles, with the major discriminant being expression of the adaptation-linked gene NPAS4.
Journal ArticleDOI
Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?
Francesco Grussu,Francesco Grussu,Torben Schneider,Torben Schneider,Carmen Tur,Richard L. Yates,Mohamed Tachrount,Andrada Ianus,Marios C. Yiannakas,Jia Newcombe,Hui Zhang,Daniel C. Alexander,Gabriele C. DeLuca,Claudia A. M. Wheeler-Kingshott,Claudia A. M. Wheeler-Kingshott +14 more
TL;DR: It is shown for the first time that neurite orientation dispersion is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology.
Journal ArticleDOI
Design and validation of diffusion MRI models of white matter.
TL;DR: A review of biophysical white matter models in use and their validation and up-to-date efforts to validate parameters estimated from biophysical models to solve the remaining open questions and converge towards consensus is presented.
Journal ArticleDOI
The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE)
Filip Szczepankiewicz,Danielle van Westen,Elisabet Englund,Carl-Fredrik Westin,Freddy Ståhlberg,Jimmy Lätt,Pia C. Sundgren,Markus Nilsson +7 more
TL;DR: DIVIDE allows non-invasive mapping of parameters that reflect variable cell eccentricity and density in brain tumors and constitutes convincing evidence that a link exists between specific aspects of tissue heterogeneity and parameters from dMRI.
Journal ArticleDOI
Evaluating fibre orientation dispersion in white matter: Comparison of diffusion MRI, histology and polarized light imaging.
Jeroen Mollink,Jeroen Mollink,M Kleinnijenhuis,Anne-Marie van Cappellen van Walsum,Stamatios N. Sotiropoulos,Stamatios N. Sotiropoulos,Michiel Cottaar,Christopher Mirfin,Christopher Mirfin,Mattias P. Heinrich,Mark Jenkinson,Menuka Pallebage-Gamarallage,Olaf Ansorge,Saad Jbabdi,Karla L. Miller +14 more
TL;DR: These results demonstrate that fibre orientation dispersion estimates from diffusion MRI represents the tissue architecture well and suggest that Dispersion models might be improved by more faithfully incorporating an informed mapping based on microscopy data.
References
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Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI
Peter J. Basser,Carlo Pierpaoli +1 more
TL;DR: Quantitative-diffusion-tensor MRI consists of deriving and displaying parameters that resemble histological or physiological stains, i.e., that characterize intrinsic features of tissue microstructure and microdynamics that are objective, and insensitive to the choice of laboratory coordinate system.
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White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI
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Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging.
TL;DR: An algorithm is presented that minimizes the bias inherent in making measurements with a fixed set of gradient vector directions by spreading out measurements in 3‐dimensional gradient vector space and this results in reduced scan times, increased precision, or improved resolution in diffusion tensor images.
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Looking into the functional architecture of the brain with diffusion MRI
TL;DR: An introduction to the key physical concepts that underlie dMRI is provided, and its potential applications in the neurosciences and associated clinical fields are reviewed.