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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Dissertation
Advanced dMRI signal modeling for tissue microstructure characterization
TL;DR: An approach allows for the estimation of time-dependent q-space indices, which quantify the time-dependence of the diffusion signal, which is called qt-dMRI.
Finsler geometry and diffusion MRI
TL;DR: The final author version and the galley proof are versions of the publication after peer review and the final published version features the final layout of the paper including the volume, issue and page numbers.
Journal ArticleDOI
Interpretable deep learning as a means for decrypting disease signature in multiple sclerosis.
Federica Cruciani,Lorenza Brusini,Mauro Zucchelli,Gustavo Retuci Pinheiro,Francesco Setti,Ilaria Boscolo Galazzo,Rachid Deriche,Leticia Rittner,Massimiliano Calabrese,Gloria Menegaz +9 more
TL;DR: The results demonstrated that dMRI features extracted in Grey Matter tissues can help in disambiguating PPMS from RRMS patients and, moreover, that LRP heatmaps highlight areas of high relevance which relate well with what is known from literature for MS disease.
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A theoretical signal processing framework for linear diffusion MRI: Implications for parameter estimation and experiment design.
TL;DR: A novel theoretical signal processing framework is introduced based on the EAP, and makes very limited modeling assumptions that can be used to characterize arbitrary linear diffusion estimation methods with arbitrary q‐space sampling, and can beused to theoretically evaluate and compare the accuracy, resolution, and noise‐resilience of different data acquisition and parameter estimation techniques.
Journal ArticleDOI
Director Field Analysis (DFA): Exploring Local White Matter Geometric Structure in Diffusion MRI.
Jian Cheng,Peter J. Basser +1 more
TL;DR: A novel mathematical framework, called Director Field Analysis (DFA), is introduced to study local geometric structural information of white matter based on the reconstructed tensor field or spherical function field and three indices to describe three types of orientational distortion in a local spatial neighborhood are proposed.
References
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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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