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Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However,…

Quantitative Methods · Quantitative Biology 2017-02-08 Ariel Rokem , Jason D. Yeatman , Franco Pestilli , Kendrick N. Kay , Aviv Mezer , Stefan van der Walt , Brian A. Wandell

All neuroimaging modalities have their own strengths and limitations. A current trend is toward interdisciplinary approaches that use multiple imaging methods to overcome limitations of each method in isolation. At the same time…

Methodology · Statistics 2023-03-30 Pratim Guha Niyogi , Martin A. Lindquist , Tapabrata Maiti

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

Motivated by recent work studying massive imaging data in the neuroimaging literature, we propose multivariate varying coefficient models (MVCM) for modeling the relation between multiple functional responses and a set of covariates. We…

Statistics Theory · Mathematics 2013-02-19 Hongtu Zhu , Runze Li , Linglong Kong

Diffusion-weighted magnetic resonance imaging (dMRI) is the only non-invasive tool for studying white matter tracts and structural connectivity of the brain. These assessments rely heavily on tractography techniques, which reconstruct…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Weide Liu , Camilo Calixto , Simon K. Warfield , Davood Karimi

Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain's structural connectivity analysis. Recent dMRI studies aim to compare connectivity patterns across subject groups and disease populations to…

We consider a sparse high-dimensional varying coefficients model with random effects, a flexible linear model allowing covariates and coefficients to have a functional dependence with time. For each individual, we observe discretely sampled…

Statistics Theory · Mathematics 2021-10-14 Michael Law , Ya'acov Ritov

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical imaging method for capturing and modeling tissue microarchitecture at a millimeter scale. A common practice to model the measured DW-MRI signal is via fiber orientation…

Purpose: Diffusion weighted MRI (dMRI) and its models of neural structure provide insight into human brain organization and variations in white matter. A recent study by McMaster, et al. showed that complex graph measures of the connectome,…

The extraction of fibers from dMRI data typically produces a large number of fibers, it is common to group fibers into bundles. To this end, many specialized distance measures, such as MCP, have been used for fiber similarity. However,…

Computer Vision and Pattern Recognition · Computer Science 2017-09-20 Kuldeep Kumar , Pietro Gori , Benjamin Charlier , Stanley Durrleman , Olivier Colliot , Christian Desrosiers

Functional linear regression analysis aims to model regression relations which include a functional predictor. The analog of the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression…

Statistics Theory · Mathematics 2011-02-28 Yichao Wu , Jianqing Fan , Hans-Georg Müller

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. One of the most common computations in dMRI involves cross-subject tract-specific analysis, whereby dMRI-derived biomarkers are compared…

Image and Video Processing · Electrical Eng. & Systems 2023-07-12 Davood Karimi , Hamza Kebiri , Ali Gholipour

Neuroimaging measures of the brain's white matter connections can enable the prediction of non-imaging phenotypes, such as demographic and cognitive measures. Existing works have investigated traditional microstructure and connectivity…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Wan Liu , Yuqian Chen , Chuyang Ye , Nikos Makris , Yogesh Rathi , Weidong Cai , Fan Zhang , Lauren J. O'Donnell

This paper proposes a physical-statistical modeling approach for spatio-temporal data arising from a class of stochastic convection-diffusion processes. Such processes are widely found in scientific and engineering applications where…

Applications · Statistics 2020-08-07 Xiao Liu , Kyongmin Yeo , Siyuan Lu

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

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that…

Methodology · Statistics 2015-06-18 Brian P. Kent , Alessandro Rinaldo , Fang-Cheng Yeh , Timothy Verstynen

Diffusion magnetic resonance imaging is an imaging technology designed to probe anatomical architectures of biological samples in an in vivo and non-invasive manner through measuring water diffusion. The contribution of this paper is…

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

We present the concept of fiber-flux density for locally quantifying white matter (WM) fiber bundles. By combining scalar diffusivity measures (e.g., fractional anisotropy) with fiber-flux measurements, we define new local descriptors…

Computer Vision and Pattern Recognition · Computer Science 2017-09-20 Itay Benou , Ronel Veksler , Alon Friedman , Tammy Riklin Raviv

Diffusion MRI tractography technique enables non-invasive visualization of the white matter pathways in the brain. It plays a crucial role in neuroscience and clinical fields by facilitating the study of brain connectivity and neurological…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Yiqiong Yang , Yitian Yuan , Baoxing Ren , Ye Wu , Yanqiu Feng , Xinyuan Zhang
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