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In recent years, diffusion models, and more generally score-based deep generative models, have achieved remarkable success in various applications, including image and audio generation. In this paper, we view diffusion models as an implicit…

Statistics Theory · Mathematics 2026-02-12 Hyeok Kyu Kwon , Dongha Kim , Ilsang Ohn , Minwoo Chae

Diffusion magnetic resonance imaging (dMRI) is a relatively modern technique used to study tissue microstructure in a non-invasive way. Non-Gaussian diffusion representation is related to the restricted diffusion and can provide information…

Signal Processing · Electrical Eng. & Systems 2020-09-17 Tomasz Pieciak , Maryam Afzali , Fabian Bogusz , Aja-Fernández , Derek K. Jones

We develop a general analytical and numerical framework for estimating intra- and extra-neurite water fractions and diffusion coefficients, as well as neurite orientational dispersion, in each imaging voxel. By employing a set of rotational…

Biological Physics · Physics 2018-04-10 Dmitry S. Novikov , Jelle Veraart , Ileana O. Jelescu , Els Fieremans

The statistical analysis of covariance matrix data is considered and, in particular, methodology is discussed which takes into account the non-Euclidean nature of the space of positive semi-definite symmetric matrices. The main motivation…

Applications · Statistics 2009-10-12 Ian L. Dryden , Alexey Koloydenko , Diwei Zhou

Diffusion tensor imaging (DTI) plays a key role in analyzing the physical structures of biological tissues, particularly in reconstructing fiber tracts of the human brain in vivo. On the one hand, eigenvalues of diffusion tensors (DTs)…

Applications · Statistics 2013-04-18 Tao Yu , Chunming Zhang , Andrew L. Alexander , Richard J. Davidson

Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique used to characterize microstructural changes in the brain. DTI studies quantify the diffusion of water molecules in a voxel using an estimated 3x3 symmetric…

Methodology · Statistics 2021-03-30 Zhou Lan , Brian J. Reich , Dipankar Bandyopadhyay

Estimating intra- and extra-axonal microstructure parameters, such as volume fractions and diffusivities, has been one of the major efforts in brain microstructure imaging with MRI. The Standard Model (SM) of diffusion in white matter has…

Diffusion MRI requires sufficient coverage of the diffusion wavevector space, also known as the q-space, to adequately capture the pattern of water diffusion in various directions and scales. As a result, the acquisition time can be…

Medical Physics · Physics 2018-07-25 Geng Chen , Bin Dong , Yong Zhang , Weili Lin , Dinggang Shen , Pew-Thian Yap

The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI) is the unique technique to obtain information about the…

Machine Learning · Computer Science 2012-07-04 Romain Giot , Christophe Charrier , Maxime Descoteaux

Spatially referenced data often have autocovariance functions with elliptical isolevel contours, a property known as geometric anisotropy. The anisotropy parameters include the tilt of the ellipse (orientation angle) with respect to a…

Statistics Theory · Mathematics 2021-10-04 Manolis P. Petrakis , Dionissios T. Hristopulos

Diffusion-weighted MRI is the forerunner of the rapidly developed microstructural MRI aimed at in vivo evaluation of the cellular tissue architecture. This brief review focuses on the spatiotemporal scales of the microstructure that are…

Medical Physics · Physics 2020-08-14 Valerij G. Kiselev

In this paper, we explore the use of the diffusion geometry framework for the fusion of geometric and photometric information in local and global shape descriptors. Our construction is based on the definition of a diffusion process on the…

Computer Vision and Pattern Recognition · Computer Science 2015-03-17 Artiom Kovnatsky , Michael M. Bronstein , Alexander M. Bronstein , Ron Kimmel

Biophysical modeling is the mediator of evaluating the cellular structure of biological tissues using diffusion-weighted MRI. It is however the bottleneck of microstructural MRI. Beyond the complexity of diffusion, the current development…

Biological Physics · Physics 2017-12-14 Bibek Dhital , Marco Reisert , Elias Kellner , Valerij G. Kiselev

The probability distribution function (PDF) of the mass surface density of molecular clouds provides essential information about the structure of molecular cloud gas and condensed structures out of which stars may form. In general, the PDF…

Astrophysics of Galaxies · Physics 2015-06-22 Jörg Fischera

We demonstrate a novel approach to the reconstruction of scanning probe x-ray diffraction tomography data with anisotropic poly crystalline samples. The method involves reconstructing a voxel map containing an orientation distribution…

We propose a new semiparametric approach for modelling nonlinear univariate diffusions, where the observed process is a nonparametric transformation of an underlying parametric diffusion (UPD). This modelling strategy yields a general class…

Econometrics · Economics 2020-05-08 Ruijun Bu , Kaddour Hadri , Dennis Kristensen

Diffusion magnetic resonance imaging datasets suffer from low Signal-to-Noise Ratio, especially at high b-values. Acquiring data at high b-values contains relevant information and is now of great interest for microstructural and…

Computer Vision and Pattern Recognition · Computer Science 2016-06-27 Samuel St-Jean , Pierrick Coupé , Maxime Descoteaux

The probability distribution function (PDF) of the mass surface density is an essential characteristic of the structure of molecular clouds or the interstellar medium in general. Observations of the PDF of molecular clouds indicate a…

Astrophysics of Galaxies · Physics 2015-06-18 Joerg Fischera

Magnetic resonance imaging technique known as DWI (diffusion-weighted imaging) allows measurement of water diffusivity on a pixel basis for evaluating pathology throughout the body and is now routinely incorporated into many body MRI…

Medical Physics · Physics 2016-11-28 Andrea Barucci , Roberto Carpi , Marco Esposito , Maristella Olmastroni , Giovanna Zatelli

We study the effect of the non-Gaussianity induced by gravitational evolution upon the statistical properties of absorption in quasar (QSO) spectra. Using the generic hierarchical ansatz and the lognormal approximation we derive the…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-03 Dipak Munshi , Peter Coles , Matteo Viel
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