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相关论文: Modeling the Shape of the Brain Connectome via Dee…

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The structural network of the brain, or structural connectome, can be represented by fiber bundles generated by a variety of tractography methods. While such methods give qualitative insights into brain structure, there is controversy over…

计算机视觉与模式识别 · 计算机科学 2022-06-15 Kristen M. Campbell , Haocheng Dai , Zhe Su , Martin Bauer , P. Thomas Fletcher , Sarang C. Joshi

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…

The brain structural connectome is generated by a collection of white matter fiber bundles constructed from diffusion weighted MRI (dMRI), acting as highways for neural activity. There has been abundant interest in studying how the…

统计方法学 · 统计学 2022-11-03 Didong Li , Phuc Nguyen , Zhengwu Zhang , David B Dunson

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

Brain network analysis plays a crucial role in diagnosing and monitoring neurodegenerative disorders such as Alzheimer's disease (AD). Existing approaches for constructing structural brain networks from diffusion tensor imaging (DTI) often…

神经元与认知 · 定量生物学 2025-05-30 Xuhang Chen , Michael Kwok-Po Ng , Kim-Fung Tsang , Chi-Man Pun , Shuqiang Wang

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

In this study, we propose a neural network approach to capture the functional connectivities among anatomic brain regions. The suggested approach estimates a set of brain networks, each of which represents the connectivity patterns of a…

计算机视觉与模式识别 · 计算机科学 2018-07-24 Baran Baris Kivilcim , Itir Onal Ertugrul , Fatos T. Yarman Vural

Diffusion-weighted magnetic resonance imaging (DWI) and fiber tractography are the only methods to measure the structure of the white matter in the living human brain. The diffusion signal has been modelled as the combined contribution from…

机器学习 · 统计学 2014-09-29 Charles Zheng , Franco Pestilli , Ariel Rokem

We present a statistical framework that jointly models brain shape and functional connectivity, which are two complex aspects of the brain that have been classically studied independently. We adopt a Riemannian modeling approach to account…

统计方法学 · 统计学 2024-04-26 Eardi Lila , John A. D. Aston

Finding an appropriate representation of dynamic activities in the brain is crucial for many downstream applications. Due to its highly dynamic nature, temporally averaged fMRI (functional magnetic resonance imaging) can only provide a…

机器学习 · 计算机科学 2022-08-18 Sikun Lin , Shuyun Tang , Scott Grafton , Ambuj Singh

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections at macro scale. Over the last two decades, the study of brain connectivity using…

Human brain connectome studies aim at extracting and analyzing relevant features associated to pathologies of interest. Usually this consists in modeling the brain connectome as a graph and in using graph metrics as features. A fine brain…

The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph theory analyses, has been very popular in the last years.…

机器学习 · 计算机科学 2020-03-13 Tiago Azevedo , Luca Passamonti , Pietro Liò , Nicola Toschi

In structural brain networks the connections of interest consist of white-matter fibre bundles between spatially segregated brain regions. The presence, location and orientation of these white matter tracts can be derived using diffusion…

神经元与认知 · 定量生物学 2012-02-09 M. Hinne , T. Heskes , M. A. J. van Gerven

Diffusion-weighted magnetic resonance imaging (DW-MRI) can be used to characterise the microstructure of the nervous tissue, e.g. to delineate brain white matter connections in a non-invasive manner via fibre tracking. Magnetic Resonance…

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

Here we show a method of directing the edges of the connectomes, prepared from diffusion tensor imaging (DTI) datasets from the human brain. Before the present work, no high-definition directed braingraphs (or connectomes) were published,…

神经元与认知 · 定量生物学 2016-09-29 Balázs Szalkai , Csaba Kerepesi , Bálint Varga , Vince Grolmusz

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

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…

In this paper, we propose a method for denoising diffusion-weighted images (DWI) of the brain using a convolutional neural network trained on realistic, synthetic MR data. We compare our results to averaging of repeated scans, a widespread…

图像与视频处理 · 电气工程与系统科学 2022-06-02 Jakub Jurek , Andrzej Materka , Kamil Ludwisiak , Agata Majos , Kamil Gorczewski , Kamil Cepuch , Agata Zawadzka
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