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We develop a flexible framework for modeling high-dimensional imaging data observed longitudinally. The approach decomposes the observed variability of repeatedly measured high-dimensional observations into three additive components: a…

In Diffusion Tensor Imaging (DTI) or High Angular Resolution Diffusion Imaging (HARDI), a tensor field or a spherical function field (e.g., an orientation distribution function field), can be estimated from measured diffusion weighted…

计算机视觉与模式识别 · 计算机科学 2017-10-17 Jian Cheng , Peter J. Basser

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,…

Estimating intra- and extra-axonal microstructure parameters, such as volume fractions and diffusivities, has been one of the major efforts in brain microstructure imaging with MRI. The Standard Model (SM) of diffusion in white matter has…

Diffusion MRI measures of the human brain provide key insight into microstructural variations across individuals and into the impact of central nervous system diseases and disorders. One approach to extract information from diffusion…

医学物理 · 物理学 2022-01-19 Qianqian Yang , David C. Reutens , Viktor Vegh

Tracking microsctructural changes in the developing brain relies on accurate inter-subject image registration. However, most methods rely on either structural or diffusion data to learn the spatial correspondences between two or more…

图像与视频处理 · 电气工程与系统科学 2020-05-15 Irina Grigorescu , Alena Uus , Daan Christiaens , Lucilio Cordero-Grande , Jana Hutter , A. David Edwards , Joseph V. Hajnal , Marc Modat , Maria Deprez

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…

计算机视觉与模式识别 · 计算机科学 2025-04-22 Shaorong Zhang , Tamoghna Chattopadhyay , Sophia I. Thomopoulos , Jose-Luis Ambite , Paul M. Thompson , Greg Ver Steeg

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…

计算机视觉与模式识别 · 计算机科学 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) 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…

计算机视觉与模式识别 · 计算机科学 2011-03-09 Miriam H. A. Bauer , Jan Egger , Daniela Kuhnt , Sebastiano Barbieri , Jan Klein , Horst K. Hahn , Bernd Freisleben , Christopher Nimsky

Brain activation mapping using functional MRI (fMRI) based on blood oxygenation level-dependent (BOLD) contrast has been conventionally focused on probing gray matter, the BOLD contrast in white matter having been generally disregarded.…

信号处理 · 电气工程与系统科学 2019-10-25 David Abramian , Martin Larsson , Anders Eklund , Hamid Behjat

Purpose: To propose a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography. Methods: We propose SuperDTI to learn the nonlinear relationship between diffusion-weighted images…

图像与视频处理 · 电气工程与系统科学 2021-07-27 Hongyu Li , Zifei Liang , Chaoyi Zhang , Ruiying Liu , Jing Li , Weihong Zhang , Dong Liang , Bowen Shen , Xiaoliang Zhang , Yulin Ge , Jiangyang Zhang , Leslie Ying

A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI) and infer properties about the white matter microstructure. However, a head-to-head…

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…

图像与视频处理 · 电气工程与系统科学 2023-07-12 Davood Karimi , Hamza Kebiri , Ali Gholipour

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,…

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…

计算机视觉与模式识别 · 计算机科学 2025-03-06 Yiqiong Yang , Yitian Yuan , Baoxing Ren , Ye Wu , Yanqiu Feng , Xinyuan Zhang

Doctors and researchers routinely use diffusion tensor imaging (DTI) and tractography to visualize the fibrous structure of tissues in the human body. This paper explores the connection of these techniques to the painterly rendering of…

图形学 · 计算机科学 2025-11-04 Alberto Di Biase

Tractography is typically performed for each subject using the diffusion tensor imaging (DTI) data in its native subject space rather than in some space common to the entire study cohort. Despite performing tractography on a population…

Portable, ultra-low-field (ULF) magnetic resonance imaging has the potential to expand access to neuroimaging but currently suffers from coarse spatial and angular resolutions and low signal-to-noise ratios. Diffusion tensor imaging (DTI),…

White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain…

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…

计算机视觉与模式识别 · 计算机科学 2024-09-23 Yui Lo , Yuqian Chen , Fan Zhang , Dongnan Liu , Leo Zekelman , Suheyla Cetin-Karayumak , Yogesh Rathi , Weidong Cai , Lauren J. O'Donnell
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