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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Posted ContentDOI
Cortical microstructural associations with CSF amyloid and pTau
TL;DR: In this paper , the authors investigated the relationship between CSF pTau 181 and Aβ 1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia.
Diffusional exchange versus microscopic kurtosis from CTI: two conflicting interpretations of the same data
TL;DR: In this paper , a heuristic approach is proposed to combine correlation tensor imaging (CTI) and MGE to estimate intra-compartmental kurtosis unconfounded by exchange and demonstrate its feasibility using numerical simulations.
Journal ArticleDOI
Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging
Journal ArticleDOI
HYDI-DSI revisited: Constrained non-parametric EAP imaging without q-space re-gridding
Antonio Tristán-Vega,Tomasz Pieciak,Guillem París,Justino R Rodríguez-Galván,Santiago Aja-Fernández +4 more
TL;DR: In this article , a Fourier Transform encoding matrix is proposed for hybrid diffusion imaging, which is adaptively designed at each voxel according to the underlying DTI approximation, so that an optimal sampling of the Ensemble Average Propagator can be pursued without being conditioned by the particular acquisition protocol.
Book ChapterDOI
Enhancing Diffusion Signal Augmentation Using Spherical Convolutions
Simon Koppers,Dorit Merhof +1 more
TL;DR: In this paper, three different ways to include spherical information: 2D projection, local spherical convolution and Fourier space transform were evaluated by considering the example of signal augmentation.
References
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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
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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
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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.