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Diffusion magnetic resonance imaging (dMRI) is a crucial non-invasive technique for exploring the microstructure of the living human brain. Traditional hand-crafted and model-based tissue microstructure reconstruction methods often require…

Image and Video Processing · Electrical Eng. & Systems 2025-02-26 Xinrui Ma , Jian Cheng , Wenxin Fan , Ruoyou Wu , Yongquan Ye , Shanshan 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

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

Alzheimer's disease (AD) is a progressive neurodegenerative disorder in which pathological changes begin many years before the onset of clinical symptoms, making early detection essential for timely intervention. T1-weighted (T1w) Magnetic…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Jason Qiu

The use of supervised deep learning techniques to detect pathologies in brain MRI scans can be challenging due to the diversity of brain anatomy and the need for annotated data sets. An alternative approach is to use unsupervised anomaly…

Image and Video Processing · Electrical Eng. & Systems 2023-03-08 Finn Behrendt , Debayan Bhattacharya , Julia Krüger , Roland Opfer , Alexander Schlaefer

Deep learning approaches for diffusion MRI have so far focused primarily on voxel-based segmentation of lesions or white-matter fiber tracts. A drawback of representing tracts as volumetric labels, rather than sets of streamlines, is that…

Image and Video Processing · Electrical Eng. & Systems 2020-09-10 Christian Ewert , David Kügler , Anastasia Yendiki , Martin Reuter

Diffusion MRI tractography is an advanced imaging technique for quantitative mapping of the brain's structural connectivity. Whole brain tractography (WBT) data contains over hundreds of thousands of individual fiber streamlines (estimated…

Image and Video Processing · Electrical Eng. & Systems 2022-07-12 Fan Zhang , Tengfei Xue , Weidong Cai , Yogesh Rathi , Carl-Fredrik Westin , Lauren J O'Donnell

Deep learning has been successful in predicting neurodegenerative disorders, such as Alzheimer's disease, from magnetic resonance imaging (MRI). Combining multiple imaging modalities, such as T1-weighted (T1) and diffusion-weighted imaging…

Artificial Intelligence · Computer Science 2026-01-30 Abhijith Shaji , Tamoghna Chattopadhyay , Sophia I. Thomopoulos , Greg Ver Steeg , Paul M. Thompson , Jose-Luis Ambite

\hspace{2mm} Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of…

Image and Video Processing · Electrical Eng. & Systems 2025-12-30 Davood Karimi , Simon K. Warfield

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial strategy for white matter (WM) parcellation. Current methods primarily use the geometric information of fibers (i.e., the spatial trajectories) to group similar fibers…

Image and Video Processing · Electrical Eng. & Systems 2024-12-17 Jin Wang , Bocheng Guo , Yijie Li , Junyi Wang , Yuqian Chen , Jarrett Rushmore , Nikos Makris , Yogesh Rathi , Lauren J O'Donnell , Fan Zhang

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

Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain in-utero. Recent studies have shown that dMRI can offer invaluable insights into the neurodevelopmental processes in the fetal stage.…

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

Accurate detection and segmentation of brain tumors from magnetic resonance imaging (MRI) are essential for diagnosis, treatment planning, and clinical monitoring. While convolutional architectures such as U-Net have long been the backbone…

Computer Vision and Pattern Recognition · Computer Science 2025-10-03 Arman Behnam

Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting early detection and implementation of prevention strategies.…

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

Ultra-low-field (ULF) MRI is emerging as an alternative modality to high-field (HF) MRI due to its lower cost, minimal siting requirements, portability, and enhanced accessibility factors that enable large-scale deployment. Although ULF-MRI…

Accurate brain tumor segmentation using multiparametric MRI is critical for effective treatment planning. However, in clinical settings, complete acquisition of all MRI sequences is not always possible. The absence of certain MRI modalities…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Danish Ali , Ajmal Mian , Naveed Akhtar , Ghulam Mubashar Hassan

Diffusion weighted MRI (dMRI) provides a non invasive virtual reconstruction of the brain's white matter structures through tractography. Analyzing dMRI measures along the trajectory of white matter bundles can provide a more specific…

Quantitative Methods · Quantitative Biology 2019-06-21 Samuel St-Jean , Maxime Chamberland , Max A. Viergever , Alexander Leemans

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