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Open AccessJournal ArticleDOI

Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure

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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.

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Citations
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Journal ArticleDOI

Generalization of diffusion magnetic resonance imaging-based brain age prediction model through transfer learning.

TL;DR: Transfer learning approach is an efficient way to generalize the dMRI-based brain age prediction model to different dMRI datasets acquired under different imaging conditions and is adopted to achieve domain adaptation.
Journal ArticleDOI

Influence of the size and curvedness of neural projections on the orientationally averaged diffusion MR signal.

TL;DR: For curvy projections, employment of longer pulse durations leads to a disappearance of the q-1 decay, while such decay is robust when narrow gradient pulses are used, and the lack of such a decay for a fibrous specimen can be seen as indicative of fibers that are curved.
Journal ArticleDOI

On the Viability of Diffusion MRI-Based Microstructural Biomarkers in Ischemic Stroke

TL;DR: 3D-SHORE indices proved to be suitable in probing plasticity in both WM and GM, further confirming their viability as a novel family of biomarkers in ischemic stroke in WM and revealing their potential exploitability in GM.
Journal ArticleDOI

Suprathreshold fiber cluster statistics: Leveraging white matter geometry to enhance tractography statistical analysis.

TL;DR: The results indicate that the STFC method gives greater sensitivity in finding group differences in white matter tract parcels compared to several traditional multiple comparison correction methods.
Journal ArticleDOI

Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

TL;DR: Model- and algorithm-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter can be well beyond commonly seen disease-related alterations.
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
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

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.
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