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相关论文: Estimating Fiber Orientation Distribution through …

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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…

应用统计 · 统计学 2016-12-23 Hao Yan , Owen Carmichael , Debashis Paul , Jie Peng

Diffusion-weighted magnetic resonance imaging (D-MRI) is an in-vivo and non-invasive imaging technology to probe anatomical architectures of biological samples. The anatomy of white matter fiber tracts in the brain can be revealed to help…

应用统计 · 统计学 2023-05-18 Jilei Yang , Seungyong Hwang , Jie Peng

Three dimensional Polarized Light Imaging (3D-PLI) is an optical technique which allows mapping the spatial fiber architecture of fibrous postmortem tissues, at sub-millimeter resolutions. Here, we propose an analytical and fast approach to…

Fiber orientation distribution (FOD) is an advanced diffusion MRI modeling technique that represents complex white matter fiber configurations, and a key step for subsequent brain tractography and connectome analysis. Its reliability and…

Identifying and characterizing brain fiber bundles can help to understand many diseases and conditions. An important step in this process is the estimation of fiber orientations using Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI).…

图像与视频处理 · 电气工程与系统科学 2024-02-20 Mateus Oliveira da Silva , Caio Pinheiro Santana , Diedre Santos do Carmo , Letícia Rittner

Data from diffusion magnetic resonance imaging (dMRI) can be used to reconstruct fiber tracts, for example, in muscle and white matter. Estimation of fiber orientations (FOs) is a crucial step in the reconstruction process and these…

计算机视觉与模式识别 · 计算机科学 2016-05-17 Chuyang Ye , Jiachen Zhuo , Rao P. Gullapalli , Jerry L. Prince

Diffusion MRI (dMRI) is a critical non-invasive technique to estimate fiber orientation distribution (FOD) for characterizing white matter integrity. Estimating FOD from single-shell low angular resolution dMRI (LAR-FOD) is limited by…

计算机视觉与模式识别 · 计算机科学 2025-12-19 Hao Tang , Hanyu Liu , Alessandro Perelli , Xi Chen , Chao Li

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…

Accurate local fiber orientation distribution (FOD) modeling based on diffusion magnetic resonance imaging (dMRI) capable of resolving complex fiber configurations benefits from specific acquisition protocols that sample a high number of…

图像与视频处理 · 电气工程与系统科学 2020-12-18 Oeslle Lucena , Sjoerd B. Vos , Vejay Vakharia , John Duncan , Keyoumars Ashkan , Rachel Sparks , Sebastien Ourselin

Fiber orientation distributions (FODs) is a popular model to represent the diffusion MRI (dMRI) data. However, imaging artifacts such as susceptibility-induced distortion in dMRI can cause signal loss and lead to the corrupted…

图像与视频处理 · 电气工程与系统科学 2024-06-21 Shuo Huang , Lujia Zhong , Yonggang Shi

Early and accurate assessment of brain microstructure using diffusion Magnetic Resonance Imaging (dMRI) is crucial for identifying neurodevelopmental disorders in neonates, but remains challenging due to low signal-to-noise ratio (SNR),…

计算机视觉与模式识别 · 计算机科学 2025-10-15 Haykel Snoussi , Davood Karimi

Diffusion magnetic resonance imaging (dMRI) is currently the only tool for noninvasively imaging the brain's white matter tracts. The fiber orientation (FO) is a key feature computed from dMRI for fiber tract reconstruction. Because the…

计算机视觉与模式识别 · 计算机科学 2017-05-22 Chuyang Ye , Jerry L. Prince

Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive method for depicting brain microstructure in vivo. Fiber orientation distributions (FODs) are mathematical representations extensively used to map white matter fiber…

图像与视频处理 · 电气工程与系统科学 2025-04-22 Rizhong Lin , Hamza Kebiri , Ali Gholipour , Yufei Chen , Jean-Philippe Thiran , Davood Karimi , Meritxell Bach Cuadra

High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber…

图像与视频处理 · 电气工程与系统科学 2021-12-07 Marica Pesce , Audrey Repetti , Anna Auría , Alessandro Daducci , Jean-Philippe Thiran , Yves Wiaux

Tractography traces the peak directions extracted from fiber orientation distribution (FOD) suffering from ambiguous spatial correspondences between diffusion directions and fiber geometry, which is prone to producing erroneous tracks while…

计算机视觉与模式识别 · 计算机科学 2024-08-20 Yuanjing Feng , Lei Xie , Jingqiang Wang , Qiyuan Tian , Jianzhong He , Qingrun Zeng , Fei Gao

Diffusion-weighted MR imaging (DWI) is the only method we currently have to measure connections between different parts of the human brain in vivo. To elucidate the structure of these connections, algorithms for tracking bundles of axonal…

机器学习 · 统计学 2014-12-05 Charles Zheng , Franco Pestilli , Ariel Rokem

Confocal histology provides an opportunity to establish intra-voxel fiber orientation distributions that can be used to quantitatively assess the biological relevance of diffusion weighted MRI models, e.g., constrained spherical…

Diffusion tractography is routinely used to study white matter architecture and brain connectivity in vivo. A key step for successful tractography of neuronal tracts is the correct identification of tract directions in each voxel. Here we…

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…

This article introduces a new methodology for reconstructing the white matter fiber pathways of brain in diffusion MRI. Usually, the signal intensity values will be lesser in the direction of higher diffusivity. The proposed approach picks…

神经元与认知 · 定量生物学 2022-07-26 Ashishi Puri , Sanjeev Kumar
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