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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 MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors…

Image and Video Processing · Electrical Eng. & Systems 2025-03-03 William Consagra , Lipeng Ning , Yogesh Rathi

Cortical surface registration is often driven by local geometric descriptors (e.g., sulcal depth and curvature). While this approach achieves geometric correspondence, it neglects the long-range wiring constraints imposed by white-matter…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Yang Xiang , Martin Cole , Zhengwu Zhang

Diffusion kurtosis imaging is an extension of diffusion tensor imaging that provides scientifically and clinically valuable information about brain tissue microstructure but suffers from poor robustness to noise, especially in voxels…

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…

Diffusion-weighted magnetic resonance imaging in brain white matter probes tissue microstructure and allows for the estimation of compartmental diffusion parameters. Recently, it became apparent that traditional single-direction diffusion…

Biological Physics · Physics 2018-09-20 Marco Reisert , Valerij G. Kiselev , Bibek Dhital

Diffusion magnetic resonance imaging, a non-invasive tool to infer white matter fiber connections, produces a large number of streamlines containing a wealth of information on structural connectivity. The size of these tractography outputs…

Computer Vision and Pattern Recognition · Computer Science 2018-04-17 Kuldeep Kumar , Kaleem Siddiqi , Christian Desrosiers

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

Over the last couple of decades, there has been a surge in various approaches to multiple-point statistics simulation, commonly referred to as MPS. These methods have aimed to improve several critical aspects of realism in the results,…

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

Mumford-Shah and Potts functionals are powerful variational models for regularization which are widely used in signal and image processing; typical applications are edge-preserving denoising and segmentation. Being both non-smooth and…

Numerical Analysis · Mathematics 2016-02-11 Andreas Weinmann , Laurent Demaret , Martin Storath

Background: Diffusion tensor imaging (DTI) has been used to characterize forearm muscle architecture. Since only uniform sampling is performed for seed points rather than fiber tracts, the tracts may be unevenly distributed in the muscle…

Image and Video Processing · Electrical Eng. & Systems 2023-06-27 Yang Li , Shihan Ma , Jiamin Zhao , Qing Li , Xinjun Sheng

Tractography algorithms are used extensively to delineate white matter structures, by operating on the voxel-wise information generated through the application of diffusion tensor imaging (DTI) or other models to diffusion weighted (DW)…

Quantitative Methods · Quantitative Biology 2024-03-05 Richard G. Carson , Alexander Leemans

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

Fiber tractography is an important tool of computational neuroscience that enables reconstructing the spatial connectivity and organization of white matter of the brain. Fiber tractography takes advantage of diffusion Magnetic Resonance…

Image and Video Processing · Electrical Eng. & Systems 2020-09-08 Tomer Weiss , Sanketh Vedula , Ortal Senouf , Oleg Michailovich , AlexBronstein

Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) is the only in vivo method to non-invasively examine the microstructure of the human heart. Current research in DT-CMR aims to improve the understanding of how the cardiac microstructure…

Image and Video Processing · Electrical Eng. & Systems 2026-05-19 Yinzhe Wu , Jiahao Huang , Fanwen Wang , Pedro Ferreira , Andrew Scott , Sonia Nielles-Vallespin , Guang Yang

Accurate segmentation of brain tissues such as gray matter and white matter from magnetic resonance imaging is essential for studying brain anatomy, diagnosing neurological disorders, and monitoring disease progression. Traditional methods,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-27 Chang Sun , Rui Shi , Tsukasa Koike , Tetsuro Sekine , Akio Morita , Tetsuya Sakai

Water diffusion gives rise to micron-scale sensitivity of diffusion MRI (dMRI) to cellular-level tissue structure. Precision medicine and quantitative imaging depend on uncovering the information content of dMRI and establishing its…

Medical Physics · Physics 2026-02-03 Santiago Coelho , Jenny Chen , Filip Szczepankiewicz , Els Fieremans , Dmitry S. Novikov

Surface-based cortical analysis is valuable for a variety of neuroimaging tasks, such as spatial normalization, parcellation, and gray matter (GM) thickness estimation. However, most tools for estimating cortical surfaces work exclusively…