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Expansion of diffusion MRI (dMRI) both into the realm of strong gradients, and into accessible imaging with portable low-field devices, brings about the challenge of gradient nonlinearities. Spatial variations of the diffusion gradients…

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

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial method for white matter (WM) parcellation to enable analysis of brains structural connectivity in health and disease. Current fiber clustering strategies primarily use…

Image and Video Processing · Electrical Eng. & Systems 2025-11-04 Bocheng Guo , Jin Wang , Yijie Li , Junyi Wang , Mingyu Gao , Puming Feng , Yuqian Chen , Jarrett Rushmore , Nikos Makris , Yogesh Rathi , Lauren J O'Donnell , Fan Zhang

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,…

Parcellation of white matter tractography provides anatomical features for disease prediction, anatomical tract segmentation, surgical brain mapping, and non-imaging phenotype classifications. However, parcellation does not always reach…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Yui Lo , Yuqian Chen , Fan Zhang , Dongnan Liu , Leo Zekelman , Suheyla Cetin-Karayumak , Yogesh Rathi , Weidong Cai , Lauren J. O'Donnell

The brain white matter consists of a set of tracts that connect distinct regions of the brain. Segmentation of these tracts is often needed for clinical and research studies. Diffusion-weighted MRI offers unique contrast to delineate these…

Image and Video Processing · Electrical Eng. & Systems 2023-07-06 Hamza Kebiri , Ali Gholipour , Meritxell Bach Cuadra , Davood Karimi

White matter structures composed of myelinated axons in the living human brain are primarily studied by diffusion-weighted MRI (dMRI). These long-range projections are typically characterized in a two-step process: dMRI is used to estimate…

Neurons and Cognition · Quantitative Biology 2017-10-09 Matthew Cieslak , Tegan Brennan , Wendy Meiring , Lukas J. Volz , Clint Greene , Alexander Asturias , Subhash Suri , Scott T. Grafton

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) 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

We present a novel method for estimation of the fiber orientation distribution (FOD) function based on diffusion-weighted Magnetic Resonance Imaging (D-MRI) data. We formulate the problem of FOD estimation as a regression problem through…

Applications · Statistics 2016-12-23 Hao Yan , Owen Carmichael , Debashis Paul , Jie Peng

Diffusion-weighted (DW) MRI measures the direction and scale of the local diffusion process in every voxel through its spectrum in q-space, typically acquired in one or more shells. Recent developments in micro-structure imaging and…

The diffusion model has recently emerged as a potent approach in computer vision, demonstrating remarkable performances in the field of generative artificial intelligence. Capable of producing high-quality synthetic images, diffusion models…

Image and Video Processing · Electrical Eng. & Systems 2025-05-14 Abdullah , Tao Huang , Ickjai Lee , Euijoon Ahn

Diffusion MRI is a neuroimaging technique measuring the anatomical structure of tissues. Using diffusion MRI to construct the connections of tissues, known as fiber tracking, is one of the most important uses of diffusion MRI. Many…

Methodology · Statistics 2019-06-18 Zhou Lan , Brian J Reich

Biophysical modeling of diffusion MRI (dMRI) offers the exciting potential of bridging the gap between the macroscopic MRI resolution and microscopic cellular features, effectively turning the MRI scanner into a noninvasive in vivo…

Diffusion Magnetic Resonance Imaging (dMRI) is an imaging technique with exquisite sensitivity to the microstructural properties of heterogeneous media. The conventionally adopted acquisition schemes involving single pulsed field gradients…

Biological Physics · Physics 2023-01-04 Deneb Boito , Cem Yolcu , Evren Özarslan

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

White matter tractography is an advanced neuroimaging technique that reconstructs the 3D white matter pathways of the brain from diffusion MRI data. It can be framed as a pathfinding problem aiming to infer neural fiber trajectories from…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Itzik Waizman , Yakov Gusakov , Itay Benou , Tammy Riklin Raviv

Tract-specific diffusion measures, as derived from brain diffusion MRI, have been linked to white matter tract structural integrity and neurodegeneration. As a consequence, there is a large interest in the automatic segmentation of white…

Image and Video Processing · Electrical Eng. & Systems 2019-08-28 Bo Li , Marius de Groot , Meike Vernooij , Arfan Ikram , Wiro Niessen , Esther Bron

It is highly desirable to know how uncertain a model's predictions are, especially for models that are complex and hard to understand as in deep learning. Although there has been a growing interest in using deep learning methods in…

Machine Learning · Computer Science 2024-08-28 Davood Karimi , Simon K. Warfield , Ali Gholipour