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相关论文: Neural Orientation Distribution Fields for Estimat…

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The Orientation Distribution Function (ODF) characterizes key brain microstructural properties and plays an important role in understanding brain structural connectivity. Recent works introduced Implicit Neural Representation (INR) based…

图像与视频处理 · 电气工程与系统科学 2024-09-17 Mohammed Munzer Dwedari , William Consagra , Philip Müller , Özgün Turgut , Daniel Rueckert , Yogesh Rathi

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…

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…

We introduce HyperDiffusionFields (HyDiF), a framework that models 3D molecular conformers as continuous fields rather than discrete atomic coordinates or graphs. At the core of our approach is the Molecular Directional Field (MDF), a…

In the last decade diffusion MRI has become a powerful tool to non-invasively study white-matter integrity in the brain. Recently many research groups have focused their attention on multi-shell spherical acquisitions with the aim of…

定量方法 · 定量生物学 2011-06-02 A. Daducci , J. D. McEwen , D. Van De Ville , J. -Ph. Thiran , Y. Wiaux

Diffusion Magnetic Resonance Imaging (DMRI) is the only non-invasive imaging technique which is able to detect the principal directions of water diffusion as well as neurites density in the human brain. Exploiting the ability of Spherical…

计算机视觉与模式识别 · 计算机科学 2017-09-04 Mauro Zucchelli , Maxime Descoteaux , Gloria Menegaz

In recent years, the field of implicit neural representation has progressed significantly. Models such as neural radiance fields (NeRF), which uses relatively small neural networks, can represent high-quality scenes and achieve…

计算机视觉与模式识别 · 计算机科学 2022-04-01 David Dadon , Ohad Fried , Yacov Hel-Or

Neural Radiance Fields (NeRF) has become a popular framework for learning implicit 3D representations and addressing different tasks such as novel-view synthesis or depth-map estimation. However, in downstream applications where decisions…

计算机视觉与模式识别 · 计算机科学 2021-09-29 Jianxiong Shen , Adria Ruiz , Antonio Agudo , Francesc Moreno-Noguer

Processing of Diffusion MRI data obtained from High Angular Resolution measurements consists of a series of steps, starting with the estimation of an orientation distribution function (ODF), which is then used as input for e.g. tractography…

数值分析 · 数学 2015-12-23 T. Hohage , C. Rügge

Diffusion-weighted magnetic resonance imaging allows for reconstruction of models for structural connectivity in the brain, such as fiber orientation distribution functions (ODFs) that describe the distribution, direction, and volume of…

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…

图像与视频处理 · 电气工程与系统科学 2025-03-03 William Consagra , Lipeng Ning , Yogesh Rathi

Streamlined qBOLD acquisitions enable experimentally straightforward observations of brain oxygen metabolism. $R_2^\prime$ maps are easily inferred; however, the Oxygen extraction fraction (OEF) and deoxygenated blood volume (DBV) are more…

图像与视频处理 · 电气工程与系统科学 2022-04-08 Ivor J. A. Simpson , Ashley McManamon , Balázs Örzsik , Alan J. Stone , Nicholas P. Blockley , Iris Asllani , Alessandro Colasanti , Mara Cercignani

A novel approach is presented for group statistical analysis of diffusion weighted MRI datasets through voxelwise Orientation Distribution Functions (ODF). Recent advances in MRI acquisition make it possible to use high quality diffusion…

The Normalizing Flow (NF) models a general probability density by estimating an invertible transformation applied on samples drawn from a known distribution. We introduce a new type of NF, called Deep Diffeomorphic Normalizing Flow (DDNF).…

机器学习 · 统计学 2018-11-26 Hadi Salman , Payman Yadollahpour , Tom Fletcher , Kayhan Batmanghelich

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

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

This paper presents Neural Visibility Field (NVF), a novel uncertainty quantification method for Neural Radiance Fields (NeRF) applied to active mapping. Our key insight is that regions not visible in the training views lead to inherently…

计算机视觉与模式识别 · 计算机科学 2024-06-18 Shangjie Xue , Jesse Dill , Pranay Mathur , Frank Dellaert , Panagiotis Tsiotras , Danfei Xu

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

Simulation-based inference provides a powerful framework for extracting rich information from nonlinear scales in current and upcoming cosmological surveys, and ensuring its robustness requires stringent validation of forward models. In…

宇宙学与河外天体物理 · 物理学 2025-08-12 Kangning Diao , Biwei Dai , Uros Seljak
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