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High-resolution diffusion tensor imaging (DTI) is beneficial for probing tissue microstructure in fine neuroanatomical structures, but long scan times and limited signal-to-noise ratio pose significant barriers to acquiring DTI at…

图像与视频处理 · 电气工程与系统科学 2021-02-19 Qiyuan Tian , Ziyu Li , Qiuyun Fan , Chanon Ngamsombat , Yuxin Hu , Congyu Liao , Fuyixue Wang , Kawin Setsompop , Jonathan R. Polimeni , Berkin Bilgic , Susie Y. Huang

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,…

Early diagnosis and noninvasive monitoring of neurological disorders require sensitivity to elusive cellular-level alterations that occur much earlier than volumetric changes observable with the millimeter-resolution of medical imaging…

The displacement distribution of a water molecular is characterized mathematically as Gaussianity without considering potential diffusion barriers and compartments. However, this is not true in real scenario: most biological tissues are…

统计计算 · 统计学 2015-07-27 Jia Liu

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),…

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological…

计算机视觉与模式识别 · 计算机科学 2024-08-06 Taohui Xiao , Jian Cheng , Wenxin Fan , Jing Yang , Cheng Li , Enqing Dong , Shanshan Wang

Many developmental processes, such as plasticity and aging, or pathological processes such as neurological diseases are characterized by modulations of specific cellular types and their microstructures. Diffusion-weighted Magnetic Resonance…

医学物理 · 物理学 2019-03-26 Marco Palombo , Noam Shemesh , Itamar Ronen , Julien Valette

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…

计算机视觉与模式识别 · 计算机科学 2026-01-21 Jason Qiu

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

Registration of diffusion MRI tractography is an essential step for analyzing group similarities and variations in the brain's white matter (WM). Streamline-based registration approaches can leverage the 3D geometric information of fiber…

计算机视觉与模式识别 · 计算机科学 2025-07-15 Junyi Wang , Mubai Du , Ye Wu , Yijie Li , William M. Wells , Lauren J. O'Donnell , Fan Zhang

We present a Bayesian probabilistic model to estimate the brain white matter atlas from high angular resolution diffusion imaging (HARDI) data. This model incorporates a shape prior of the white matter anatomy and the likelihood of…

计算机视觉与模式识别 · 计算机科学 2013-10-14 Jia Du , Alvina Goh , Anqi Qiu

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

Connectivity information derived from diffusion-weighted magnetic resonance images~(DW-MRIs) plays an important role in studying human subcortical gray matter structures. However, due to the $O(N^2)$ complexity of computing the connectivity…

图像与视频处理 · 电气工程与系统科学 2023-02-21 Zhangxing Bian , Muhan Shao , Jiachen Zhuo , Rao P. Gullapalli , Aaron Carass , Jerry L. Prince

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 increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis…

计算机视觉与模式识别 · 计算机科学 2024-03-06 Camilo Calixto , Camilo Jaimes , Matheus D. Soldatelli , Simon K. Warfield , Ali Gholipour , Davood Karimi

Tract-specific diffusion measures, as derived from brain diffusion MRI, have been linked to white matter tract structural integrity and neurodegeneration. As a consequence, there is a large interest in the automatic segmentation of white…

图像与视频处理 · 电气工程与系统科学 2019-08-28 Bo Li , Marius de Groot , Meike Vernooij , Arfan Ikram , Wiro Niessen , Esther Bron

Diffusion-weighted magnetic resonance imaging (DW-MRI) allows for non-invasive imaging of the local fiber architecture of the human brain at a millimetric scale. Multiple classical approaches have been proposed to detect both single (e.g.,…

White matter structures composed of myelinated axons in the living human brain are primarily studied by diffusion-weighted MRI (dMRI). These long-range projections are typically characterized in a two-step process: dMRI is used to estimate…

Diffusion MRI offers a unique probe into neural microstructure and connectivity in the developing brain. However, analysis of neonatal brain imaging data is complicated by inevitable subject motion, leading to a series of scattered slices…

Diffusion-based algorithms have emerged as promising techniques for weight generation. However, existing solutions are limited by two challenges: generalizability and local target assignment. The former arises from the inherent lack of…

机器学习 · 计算机科学 2025-05-20 Yunchuan Guan , Yu Liu , Ke Zhou , Zhiqi Shen , Jenq-Neng Hwang , Lei Li