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Magnetoacoustic tomography with magnetic induction (MAT-MI) is a coupled-physics medical imaging modality for determining conductivity distribution in biological tissue. The capability of MAT-MI to provide high resolution images has been…

数值分析 · 数学 2015-03-13 Lingyun Qiu , Fadil Santosa

Diffusional Kurtosis Imaging (DKI) is a sensitive biomarker for microstructure in health and disease. However, DKI is not specific to any microstructural property since it may emerge from several different sources. Q-space trajectory…

医学物理 · 物理学 2020-03-06 Rafael Neto Henriques , Sune Nørhøj Jespersen , Noam Shemesh

Statistical analysis of Diffusion Tensor Imaging (DTI) data requires a computational framework that is both numerically tractable (to account for the high dimensional nature of the data) and geometric (to account for the nonlinear nature of…

计算机视觉与模式识别 · 计算机科学 2012-10-11 Anne Collard , Silvère Bonnabel , Christophe Phillips , Rodolphe Sepulchre

Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time/frequency-dependent ("restricted") and anisotropic self-diffusion of water.…

Diffusion tensor imaging (DTI) is a popular magnetic resonance imaging technique used to characterize microstructural changes in the brain. DTI studies quantify the diffusion of water molecules in a voxel using an estimated 3x3 symmetric…

统计方法学 · 统计学 2021-03-30 Zhou Lan , Brian J. Reich , Dipankar Bandyopadhyay

Biaxial anisotropy, arising from distinct optical responses along three principal directions, underlies the complex structure of many crystalline, polymeric, and biological materials. However, existing techniques such as X-ray diffraction…

We provide a mathematical analysis and a numerical framework for magnetoacoustic tomography with magnetic induction. The imaging problem is to reconstruct the conductivity distribution of biological tissue from measurements of the Lorentz…

偏微分方程分析 · 数学 2015-08-05 Habib Ammari , Simon Boulier , Pierre Millien

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…

生物物理 · 物理学 2023-01-04 Deneb Boito , Cem Yolcu , Evren Özarslan

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-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…

计算机视觉与模式识别 · 计算机科学 2024-09-17 Sheng Chen , Zihao Tang , Mariano Cabezas , Xinyi Wang , Arkiev D'Souza , Michael Barnett , Fernando Calamante , Weidong Cai , Chenyu Wang

Magneto-acousto-electric tomography (MAET) combines ultrasound with a static magnetic field to infer the electrical conductivity of an object. In this paper, we present a rigorous quasi-static mathematical model for MAET with magnetic field…

偏微分方程分析 · 数学 2026-03-03 Lingyun Qiu , Siqin Zheng

Diffusion tensor imaging (DTI) is a novel modality of magnetic resonance imaging that allows noninvasive mapping of the brain's white matter. A particular map derived from DTI measurements is a map of water principal diffusion directions,…

应用统计 · 统计学 2008-12-18 Armin Schwartzman , Robert F. Dougherty , Jonathan E. Taylor

Diffusion magnetic resonance imaging (dMRI) is an emerging medical technique used for describing water diffusion in an organic tissue. Typically, rank-2 tensors quantify this diffusion. From this quantification, it is possible to calculate…

计算机视觉与模式识别 · 计算机科学 2016-06-28 Hernan Dario Vargas Cardona , Mauricio A. Alvarez , Alvaro A. Orozco

Diffusion tensor imaging (DTI) plays a key role in analyzing the physical structures of biological tissues, particularly in reconstructing fiber tracts of the human brain in vivo. On the one hand, eigenvalues of diffusion tensors (DTs)…

应用统计 · 统计学 2013-04-18 Tao Yu , Chunming Zhang , Andrew L. Alexander , Richard J. Davidson

Diffusion anisotropy in diffusion tensor imaging (DTI) is commonly quantified with normalized diffusion anisotropy indices (DAIs). Most often, the fractional anisotropy (FA) is used, but several alternative DAIs have been introduced in…

Dielectric tensor tomography is an imaging technique for mapping three-dimensional distributions of dielectric properties in transparent materials. This work introduces an enhanced illumination strategy employing a micro-electromechanical…

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model. Volumetric scalar metrics including fractional anisotropy,…

图像与视频处理 · 电气工程与系统科学 2022-11-01 Zihao Tang , Xinyi Wang , Lihaowen Zhu , Mariano Cabezas , Dongnan Liu , Michael Barnett , Weidong Cai , Chengyu Wang

We present numerical reconstructions of anisotropic conductivity tensors in three dimensions, from knowledge of a finite family of power density functionals. Such a problem arises in the coupled-physics imaging modality Ultrasound Modulated…

数值分析 · 数学 2018-06-13 François Monard , Donsub Rim

We developed a novel contactless frequency-domain approach to study thermal transport, which is particularly convenient when thermally anisotropic materials are considered. The method is based on a similar line-shaped heater geometry as…

Diffusion tensor imaging (DTI) holds significant importance in clinical diagnosis and neuroscience research. However, conventional model-based fitting methods often suffer from sensitivity to noise, leading to decreased accuracy in…

计算机视觉与模式识别 · 计算机科学 2024-09-05 Jialong Li , Zhicheng Zhang , Yunwei Chen , Qiqi Lu , Ye Wu , Xiaoming Liu , QianJin Feng , Yanqiu Feng , Xinyuan Zhang
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