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
Reads0
Chats0
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
Citations
More filters
Visualization and Processing of Higher Order Descriptors for Multi-Valued Data (Dagstuhl Seminar 14082)
TL;DR: The focus of the seminar was to discuss modern and emerging methods for analysis and visualization of tensor and higher order descriptors from medical imaging and engineering applications.
Proceedings ArticleDOI
Can Single Shell Diffusion MRI Detect Synaptic Plasticity in Mice
Lorenza Brusini,Federica Cruciani,I. Boscolo Galazzo,A. Galbusera,M. Borin,G. Paolone,G. Diana,Mario Rosario Buffelli,Alessandro Gozzi,Gloria Menegaz +9 more
TL;DR: The data suggest that mouse morphoanatomical imaging is sensitive to changes in neural plasticity, and an increment of both Fractional Anisotropy (FA) and Axial Diffusivity (AD) and a decrement of both Mean Diffusiveness (MD) and Return To Plane Probability (RTPP) mainly in the visual and hippocampal areas.
Proceedings ArticleDOI
Representing, Sampling and Reconstructing Diffusion MRI Signal in Space and Time
TL;DR: The proposed 4D-basis, sampling grid and corresponding transforms for representing, sampling and reconstructing the diffusion MRI signal that is a function of both the diffusion wave vector q and diffusion time $\tau$.
Journal ArticleDOI
Editorial for "Unraveling the MRI-Based Microstructural Signatures Behind Primary Progressive and Relapsing-Remitting Multiple Sclerosis Phenotypes".
TL;DR: The authors found the PPMS group to have significantly higher age, disease duration, and EDSS scores as compared to RRMS, and group comparisons using dMRI microstructural measures found MD and MSD to be hyperintense in unrestricted diffusion regions of the brain such as the cerebrospinal fluid.
Book ChapterDOI
Finslerian Diffusion and the Bloch–Torrey Equation
TL;DR: The main contribution of this work is the conclusion that simply considering Brownian motion on the Finsler base manifold does not reproduce the signal model proposed in the FINSlerian framework, nor lead to a model that allows the extraction of the F Inslerian metric structure from the signal.
References
More filters
Book
Table of Integrals, Series, and Products
TL;DR: Combinations involving trigonometric and hyperbolic functions and power 5 Indefinite Integrals of Special Functions 6 Definite Integral Integral Functions 7.Associated Legendre Functions 8 Special Functions 9 Hypergeometric Functions 10 Vector Field Theory 11 Algebraic Inequalities 12 Integral Inequality 13 Matrices and related results 14 Determinants 15 Norms 16 Ordinary differential equations 17 Fourier, Laplace, and Mellin Transforms 18 The z-transform
Book
Compressed sensing
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
A table of integrals
TL;DR: Basic Forms x n dx = 1 n + 1 x n+1 (1) 1 x dx = ln |x| (2) udv = uv − vdu (3) 1 ax + bdx = 1 a ln|ax + b| (4) Integrals of Rational Functions
Journal ArticleDOI
Spin diffusion measurements : spin echoes in the presence of a time-dependent field gradient
E. O. Stejskal,J. E. Tanner +1 more
TL;DR: In this article, a derivation of the effect of a time-dependent magnetic field gradient on the spin-echo experiment, particularly in the presence of spin diffusion, is given.
Book
Solving least squares problems
TL;DR: Since the lm function provides a lot of features it is rather complicated so it is going to instead use the function lsfit as a model, which computes only the coefficient estimates and the residuals.