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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

Geostatistical modeling for continuous point-referenced data has been extensively applied to neuroimaging because it produces efficient and valid statistical inference. However, diffusion tensor imaging (DTI), a neuroimaging characterizing…

Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and…

Methodology · Statistics 2017-07-24 Dario Gasbarra , Sinisa Pajevic , Peter J. Basser

Diffusion Tensor Imaging (DTI) is a non-invasive imaging technique that allows estimation of the location of white matter tracts in-vivo, based on the measurement of water diffusion properties. For each voxel, a second-order tensor can be…

Computer Vision and Pattern Recognition · Computer Science 2013-10-24 Miriam H. A. Bauer , Sebastiano Barbieri , Jan Klein , Jan Egger , Daniela Kuhnt , Bernd Freisleben , Horst K. Hahn , Christopher Nimsky

Diffusion tensor imaging (DTI) is a widely used method for studying brain white matter development and degeneration. However, standard DTI estimation methods depend on a large number of high-quality measurements. This would require long…

Image and Video Processing · Electrical Eng. & Systems 2022-11-16 Davood Karimi , Ali Gholipour

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) holds significant importance in clinical diagnosis and neuroscience research. However, conventional model-based fitting methods often suffer from sensitivity to noise, leading to decreased accuracy in…

Computer Vision and Pattern Recognition · Computer Science 2024-09-05 Jialong Li , Zhicheng Zhang , Yunwei Chen , Qiqi Lu , Ye Wu , Xiaoming Liu , QianJin Feng , Yanqiu Feng , Xinyuan Zhang

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model. Volumetric scalar metrics including fractional anisotropy,…

Image and Video Processing · Electrical Eng. & Systems 2022-11-01 Zihao Tang , Xinyi Wang , Lihaowen Zhu , Mariano Cabezas , Dongnan Liu , Michael Barnett , Weidong Cai , Chengyu Wang

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive tool for watching the microstructure of fibrous nerve and muscle tissue. From dMRI, it is possible to estimate 2-rank diffusion tensors imaging (DTI) fields, that are widely used…

Computer Vision and Pattern Recognition · Computer Science 2016-06-28 Hernan Dario Vargas Cardona , Mauricio A. Alvarez , Alvaro A. Orozco

Diffusion-weighted imaging (DWI) is a type of Magnetic Resonance Imaging (MRI) technique sensitised to the diffusivity of water molecules, offering the capability to inspect tissue microstructures and is the only in-vivo method to…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Sheng Chen , Zihao Tang , Mariano Cabezas , Xinyi Wang , Arkiev D'Souza , Michael Barnett , Fernando Calamante , Weidong Cai , Chenyu Wang

Diffusion Tensor Imaging (DTI) allows estimating the position, orientation and dimension of bundles of nerve pathways. This non-invasive imaging technique takes advantage of the diffusion of water molecules and determines the diffusion…

Computer Vision and Pattern Recognition · Computer Science 2011-03-09 Miriam H. A. Bauer , Jan Egger , Daniela Kuhnt , Sebastiano Barbieri , Jan Klein , Horst K. Hahn , Bernd Freisleben , Christopher Nimsky

Magnetic resonance diffusion tensor imaging (DTI) is a critical tool for neural disease diagnosis. However, long scan time greatly hinders the widespread clinical use of DTI. To accelerate image acquisition, a feature-enhanced joint…

Image and Video Processing · Electrical Eng. & Systems 2024-05-28 Lang Zhang , Jinling He , Dong Liang , Hairong Zheng , Yanjie Zhu

Diffusion tensor imaging (DTI) is a novel modality of magnetic resonance imaging that allows noninvasive mapping of the brain's white matter. A particular map derived from DTI measurements is a map of water principal diffusion directions,…

Applications · Statistics 2008-12-18 Armin Schwartzman , Robert F. Dougherty , Jonathan E. Taylor

Diffusion tensor imaging (DTI) provides crucial insights into the microstructure of the human brain, but it can be time-consuming to acquire compared to more readily available T1-weighted (T1w) magnetic resonance imaging (MRI). To address…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Shaorong Zhang , Tamoghna Chattopadhyay , Sophia I. Thomopoulos , Jose-Luis Ambite , Paul M. Thompson , Greg Ver Steeg

Diffusion Tensor Imaging (DTI) is an effective tool for the analysis of structural brain connectivity in normal development and in a broad range of brain disorders. However efforts to derive inherent characteristics of structural brain…

Computational Engineering, Finance, and Science · Computer Science 2018-02-14 Yu Jin , Joseph F. JaJa , Rong Chen , Edward H. Herskovits

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various works have used diffusion MRI for automatic classification of AD. However, classification performance obtained with different approaches is…

Diffusion tensor imaging (DTI) has been used to study the effects of neurodegenerative diseases on neural pathways, which may lead to more reliable and early diagnosis of these diseases as well as a better understanding of how they affect…

Computer Vision and Pattern Recognition · Computer Science 2021-12-15 Chaoqing Xu , Tyson Neuroth , Takanori Fujiwara , Ronghua Liang , Kwan-Liu Ma

We consider settings where the observations are drawn from a zero-mean multivariate (real or complex) normal distribution with the population covariance matrix having eigenvalues of arbitrary multiplicity. We assume that the eigenvectors of…

Statistics Theory · Mathematics 2009-01-22 N. Raj Rao , James A. Mingo , Roland Speicher , Alan Edelman

In vivo cardiac diffusion tensor imaging (cDTI) is a promising Magnetic Resonance Imaging (MRI) technique for evaluating the micro-structure of myocardial tissue in the living heart, providing insights into cardiac function and enabling the…

We study variance reduction for score estimation and diffusion-based sampling in settings where the clean (target) score is available or can be approximated. Starting from the Target Score Identity (TSI), which expresses the noisy marginal…

Machine Learning · Statistics 2026-01-26 Alois Duston , Tan Bui-Thanh
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