检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

180 篇 会议
73 册 图书

馆藏范围

250 篇 电子文献
6 种 纸本馆藏

日期分布

学科分类号

118 篇 理学
- 117 篇 数学
- 19 篇 生物学
- 16 篇 统计学（可授理学、...
- 1 篇 物理学
112 篇 医学
- 85 篇 特种医学
- 54 篇 临床医学
- 44 篇 医学技术（可授医学...
58 篇 工学
- 52 篇 计算机科学与技术...
- 2 篇 机械工程
- 2 篇 仪器科学与技术
- 2 篇 控制科学与工程
- 2 篇 软件工程
- 1 篇 建筑学
3 篇 艺术学
- 3 篇 设计学（可授艺术学...

主题

35 篇 visualization
22 篇 diffusion mri
15 篇 image processing...
14 篇 computer graphic...
12 篇 magnetic resonan...
11 篇 topology
10 篇 tractography
10 篇 diffusion
9 篇 geometry
8 篇 deep learning
8 篇 artificial intel...
6 篇 computational ma...
6 篇 computational sc...
6 篇 computer imaging...
5 篇 mathematical and...
5 篇 eye tracking
5 篇 tensors
5 篇 eye movements
4 篇 simulation and m...
4 篇 pattern recognit...

机构

5 篇 university of ka...
4 篇 univ pavia dept ...
4 篇 univ cote dazur ...
4 篇 northwestern pol...
4 篇 univ n carolina ...
4 篇 university colle...
4 篇 univ n carolina ...
3 篇 ucl ctr med imag...
3 篇 linköping univer...
3 篇 lawrence livermo...
3 篇 zuse institute b...
3 篇 university of ca...
3 篇 univ verona comp...
3 篇 inria sophia ant...
3 篇 univ n carolina ...
3 篇 wright state uni...
3 篇 the university o...
3 篇 univ n carolina ...
3 篇 ecole polytech f...
3 篇 therapanacea

作者

10 篇 deriche rachid
8 篇 yap pew-thian
8 篇 hans hagen
7 篇 hans-christian h...
7 篇 shen dinggang
6 篇 wassermann demia...
6 篇 enrico kaden
6 篇 chen geng
6 篇 bernd hamann
5 篇 jones derek k.
5 篇 hamish carr
5 篇 thompson paul m.
5 篇 fick rutger
5 篇 marco reisert
5 篇 pizzolato marco
5 篇 pascucci valerio
5 篇 yogesh rathi
4 篇 julien tierny
4 篇 thiran jean-phil...
4 篇 nir talia m.

语言

244 篇 英文
9 篇 中文

检索条件"丛书名=Mathematics and Visualization"

共 253 条记录，以下是41-50 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Spatial Characterisation of Fibre Response Functions for Spherical Deconvolution in Multiple Sclerosis

Spatial Characterisation of Fibre Response Functions for Sph...

引用

21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) / 8th Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM) / International Workshop on Computational Diffusion MRI (CDMRI)

作者： Tur, Carmen Grussu, Francesco Prados, Ferran Collorone, Sara Wheeler-Kingshott, Claudia A. M. Gandini Ciccarelli, Olga UCL Fac Brain Sci Dept Neuroinflammat Queen Sq Inst NeurolQueen Sq MS Ctr London England UCL Ctr Med Image Comp Dept Comp Sci London England UCL Ctr Med Image Comp Dept Med Phys & Biomed Engn London England Univ Pavia Dept Brain & Behav Sci Pavia Italy IRCCS Mondino Fdn Brain MRI 3T Res Ctr Pavia Italy Univ Coll London Hosp Natl Inst Hlth Res Biomed Res Ctr London England

ISBN: (纸本)9783030058319;9783030058302

Brain tractography based on diffusion-weighted (DW) MRI data has been increasingly used to investigate crucial pathophysiological aspects of several neurological conditions, including multiple sclerosis (MS). The advent of fibre tracking methods based on constrained spherical deconvolution (CSD), which recovers the fibre orientation distribution function (fODF) by performing a single-kernel (or uniform-kernel) deconvolution of the measured DW signals with non-negativity constraints, has meant an important breakthrough. However, it is unclear whether using a uniform kernel deconvolution of the measured DW signals for the whole brain is appropriate, especially in pathology. In this study, our main aim was to explore the validity of using a uniform fibre kernel for spherical deconvolution in a cohort of 19 patients with a first inflammatory-demyelinating attack of the central nervous system suggestive of MS and 12 age-matched healthy controls. In particular, considering that the number of peaks is a key feature the fODF and is known to impact directly on downstream fibre tracking, we assessed the association between patient-wise mean number of (fODF) peaks in the non-lesional white matter obtained with a uniform kernel and the bias or differences in the estimation of local diffusion properties when a uniform kernel (instead of a locally-fitted voxel-wise kernel) was used. Finally, in order to support our in-vivo results, we performed a simulation analysis to further assess the theoretical impact of using a uniform kernel. Our in-vivo results showed non-significant trends towards an influence of the bias in the estimation of the local diffusion properties when a uniform kernel was used on the number of peaks. In the simulation analysis, a clear association was observed between such bias and the number of peaks. All this suggests that the use of a uniform kernel to estimate the fODFs at the voxel level may not be adequate. However, we acknowledge that the approach follow

关键词： Fibre response function Connectivity analysis Multiple sclerosis

来源：评论

学校读者我要写书评

暂无评论

Dmipy, A Diffusion Microstructure Imaging Toolbox in Python to Improve Research Reproducibility

Dmipy, A Diffusion Microstructure Imaging Toolbox in Python ...

引用

作者： Alimi, Abib Fick, Rutger Wassermann, Demian Deriche, Rachid Univ Cote dAzur Inria Athena Sophia Antipolis France TheraPanacea Paris France Univ Paris Saclay Inria Parietal CEA Paris France

ISBN: (纸本)9783030058319;9783030058302

Non-invasive estimation of brain white matter microstructure features using diffusion MRI-otherwise known as Microstructure Imaging-has become an increasingly diverse and complicated field over the last decade. Multi-compartment-based models have been a popular approach to estimate these features. In this work, we present Diffusion Microstructure Imaging in Python (Dmipy), a diffusion MRI toolbox which allows accessing any multi-compartment-based model and robustly estimates these important features from single-shell, multi-shell, and multidiffusion time, and multi-TE data. Dmipy follows a building block-based philosophy to microstructure imaging, meaning a multi-compartment model can be constructed and fitted to dMRI data using any combination of underlying tissue models, axon dispersion-or diameter distributions, and optimization algorithms using less than 10 lines of code, thus helps improve research reproducibility. In describing the toolbox, we show how Dmipy enables to easily design microstructure models and offers to the users the freedom to choose among different optimization strategies. We finally present three advanced examples of highly complex modeling approaches which are made easy using Dmipy.

关键词： Diffusion MRI Microstructure imaging dMRI Multi-compartment models Python Free open source software

来源：评论

学校读者我要写书评

暂无评论

Diffusion MRI Outside the Brain

Diffusion MRI Outside the Brain

引用

作者： Nunes, Rita G. Nogueira, Luisa Gaspar, Andreia S. Adubeiro, Nuno Brandao, Sofia Univ Lisbon Inst Syst & Robot LARSYS Inst Super Tecn Lisbon Portugal Univ Lisbon Dept Bioengn Inst Super Tecn Lisbon Portugal Polytech Porto ESS PPorto Sch Hlth Dept Radiol Porto Portugal Univ Porto Inst Biomed Sci Abel Salazar ICBAS Porto Portugal Univ Porto Fac Med Ctr Hosp Sao Joao EPE Dept Radiol Porto Portugal CRL Adv Inst Hlth Sci CESPU Gandra Paredes Portugal Univ Porto Associated Lab Energy Transports & Aeronaut LAETA Inst Sci & Innovat Mech & Ind Engn INEGI Fac Engn Porto Portugal

ISBN: (纸本)9783030058319;9783030058302

This manuscript provides an overview of recent developments in Diffusion-Weighted Imaging (DWI) outside the brain, focusing on liver, breast, prostate, muskuloskeletal (MSK) and cardiac applications. A general introduction to crosscutting acquisition and image processing challenges is first provided. These often include short T-2 relaxation times, the need to image a large field-of-view with the resulting complications in shimming the B0 field and achieving good fat suppression. Some of the strategies developed for dealing with motion, namely cardiac and respiratory motion are described. Specific sections are then presented for each of the aforementioned organs. A motivation for the clinical applicability of DWI is first provided, followed by specific image acquisition and processing considerations. Quantitative imaging is becoming standard in clinical practice, and the Apparent Diffusion Coefficient is routinely estimated in the liver, breast and prostate. Application of alternative signal models in these organs is being explored, including both the Intravoxel Incoherent Motion and Diffusion Kurtosis models. Ongoing efforts are focused on evaluating the potential clinical added value of the extra parameters and on improving their repeatability. MSK and cardiac DWI have shown potential for assessing pathological changes in fiber architecture, but further validation is required to enable application in the clinical setting.

关键词： Diffusion-weighted MRI Liver Breast Prostate Muskuloskeletal system Cardiac Applications

来源：评论

学校读者我要写书评

暂无评论

Voxel-Wise Clustering of Tractography Data for Building Atlases of Local Fiber Geometry

Voxel-Wise Clustering of Tractography Data for Building Atla...

引用

作者： Brusini, Irene Jorgens, Daniel Smedby, Orjan Moreno, Rodrigo KTH Royal Inst Technol Dept Biomed Engn & Hlth Syst Stockholm Sweden Karolinska Inst Dept Neurobiol Care Sci & Soc Stockholm Sweden

ISBN: (纸本)9783030058319;9783030058302

This paper aims at proposing a method to generate atlases of white matter fibers' geometry that consider local orientation and curvature of fibers extracted from tractography data. Tractography was performed on diffusion magnetic resonance images from a set of healthy subjects and each tract was characterized voxel-wise by its curvature and Frenet-Serret frame, based on which similar tracts could be clustered separately for each voxel and each subject. Finally, the centroids of the clusters identified in all subjects were clustered to create the final atlas. The proposed clustering technique showed promising results in identifying voxel-wise distributions of curvature and orientation. Two tractography algorithms (one deterministic and one probabilistic) were tested for the present work, obtaining two different atlases. A high agreement between the two atlases was found in several brain regions. This suggests that more advanced tractography methods might only be required for some specific regions in the brain. In addition, the probabilistic approach resulted in the identification of a higher number of fiber orientations in various white matter areas, suggesting it to be more adequate for investigating complex fiber configurations in the proposed framework as compared to deterministic tractography.

关键词： Tractography Fiber clustering Brain atlases

来源：评论

学校读者我要写书评

暂无评论

Inference of an Extended Short Fiber Bundle Atlas Using Sulcus-Based Constraints for a Diffeomorphic Inter-subject Alignment

Inference of an Extended Short Fiber Bundle Atlas Using Sulc...

引用

作者： Avila, Nicole Labra Lebenberg, Jessica Riviere, Denis Auzias, Guillaume Fischer, Clara Poupon, Fabrice Guevara, Pamela Poupon, Cyril Mangin, Jean-Francois CEA DRF Neurospin UNATI Gif Sur Yvette France Univ Paris Sud Paris Saclay France Univ Paris Diderot Sorbonne Paris Cite UMR S 1161 INSERM Paris France Aix Marseille Univ Inst Neurosci la Timone Marseille France Univ Concepcion Concepcion Chile CEA DRF Neurospin UNIRS Gif Sur Yvette France

ISBN: (纸本)9783030058319;9783030058302

We present a new framework for the creation of an extended atlas of short fiber bundles between 20 and 80 mm length. This method uses a Diffeomorphic inter-subject alignment procedure including information of cortical foldings and forces the accurate match of the sulci that have to be circumvented by the U-bundles. Then, a clustering is performed to extract the most reproducible bundles across subjects. First results show an increased number of U-bundles consistently mapped in the general population compared with previous atlases created from the same database. Future analysis over this new extended Brain atlas may improve our understanding of the relationship between the folding pattern and the U-bundle variability. The ultimate aim will be the possibility to detect abnormal configurations induced by developmental issues.

关键词： White matter U-fiber U-bundles Short fiber bundles dMRI Diffusion MRI Brain atlas Bundle atlas Diffeomorphic alignment Sulcus base alignment Cortical folding pattern Sulci

来源：评论

学校读者我要写书评

暂无评论

A Closed-Form Solution of Rotation Invariant Spherical Harmonic Features in Diffusion MRI

A Closed-Form Solution of Rotation Invariant Spherical Harmo...

引用

作者： Zucchelli, Mauro Deslauriers-Gauthier, Samuel Deriche, Rachid Inria Sophia Antipolis Mediterranee Athena Project Team Biot France

ISBN: (纸本)9783030058319;9783030058302

Rotation invariant features are an indispensable tool for characterizing diffusion Magnetic Resonance Imaging (MRI) and in particular for brain tissue microstructure estimation. In this work, we propose a new mathematical framework for efficiently calculating a complete set of such invariants from any spherical function. Specifically, our method is based on the spherical harmonics series expansion of a given function of any order and can be applied directly to the resulting coefficients by performing a simple integral operation analytically. This enable us to derive a general closed-form equation for the invariants. We test our invariants on the diffusion MRI fiber orientation distribution function obtained from the diffusion signal both in-vivo and in synthetic data. Results show how it is possible to use these invariants for characterizing the white matter using a small but complete set of features.

关键词： Diffusion MRI Rotation invariant Gaunt coefficients Spherical harmonics

来源：评论

学校读者我要写书评

暂无评论

Measures of Tractography Convergence

Measures of Tractography Convergence

引用

作者： Moyer, Daniel C. Thompson, Paul Ver Steeg, Greg Univ Southern Calif Imaging Genet Ctr Stevens Inst Neuroimaging & Informat Los Angeles CA 90007 USA Informat Sci Inst Marina Del Rey CA 90292 USA

ISBN: (纸本)9783030058319;9783030058302

In the present work, we use information theory to understand the empirical convergence rate of tractography, a widely-used approach to reconstruct anatomical fiber pathways in the living brain. Based on diffusion MRI data, tractography is the starting point for many methods to study brain connectivity. Of the available methods to perform tractography, most reconstruct a finite set of streamlines, or 3D curves, representing probable connections between anatomical regions, yet relatively little is known about how the sampling of this set of streamlines affects downstream results, and how exhaustive the sampling should be. Here we provide a method to measure the information theoretic surprise (self-cross entropy) for tract sampling schema. We then empirically assess four streamline methods. We demonstrate that the relative information gain is very low after a moderate number of streamlines have been generated for each tested method. The results give rise to several guidelines for optimal sampling in brain connectivity analyses.

关键词： Tractography Cross entropy Simulation

来源：评论

学校读者我要写书评

暂无评论

Tissue Segmentation Using Sparse Non-negative Matrix Factorization of Spherical Mean Diffusion MRI Data

Tissue Segmentation Using Sparse Non-negative Matrix Factori...

引用

作者： Sun, Peng Wu, Ye Chen, Geng Wu, Jun Shen, Dinggang Yap, Pew-Thian Univ N Carolina Dept Radiol Chapel Hill NC 27515 USA Univ N Carolina BRIC Chapel Hill NC 27515 USA Northwestern Polytech Univ Sch Comp Sci Xian Shaanxi Peoples R China Zhejiang Univ Technol Inst Informat Proc & Automat Hangzhou Zhejiang Peoples R China Northwestern Polytech Univ Sch Elect & Informat Xian Shaanxi Peoples R China

ISBN: (纸本)9783030058319;9783030058302

In this paper, we present a method based on sparse non-negative matrix factorization (NMF) for brain tissue segmentation using diffusion MRI (DMRI) data. Unlike existing NMF-based approaches, in our method NMF is applied to the spherical mean data, computed on a per-shell basis, instead of the original diffusion-weighted images. This is motivated by the fact that the spherical mean is independent of the fiber orientation distribution and is only dependent on tissue microstructure. Applying NMF to the spherical mean data will hence allow tissue signal separation based solely on the microstructural properties, unconfounded by factors such as fiber dispersion and crossing. We show results explaining why applying NMF directly on the diffusion-weighted images fails and why our method is able to yield the expected outcome, producing tissue segmentation with greater accuracy.

关键词： Tissue segmentation Sparse NMF Spherical mean Diffusion MRI

来源：评论

学校读者我要写书评

暂无评论

Challenges and Opportunities in dMRI Data Harmonization

Challenges and Opportunities in dMRI Data Harmonization

引用

作者： Zhu, Alyssa H. Moyer, Daniel C. Nir, Talia M. Thompson, Paul M. Jahanshad, Neda Univ Southern Calif Imaging Genet Ctr Stevens Neuroimaging & Informat Inst Keck Sch Med Marina Del Rey CA 90292 USA

ISBN: (纸本)9783030058319;9783030058302

Advances in diffusion MRI (dMRI) have led to discoveries of factors that affect brain microstructure and connectivity in health and disease. The small size of many neuroimaging studies led to concerns about poor reproducibility of research findings, and calls for the comparison and pooling of multi-cohort datasets to establish the consistency of reported effects. Across studies diffusion MRI protocols vary in spatial, angular and q-space resolution, b-value, as well as hardware used-all of which affect measured diffusion parameters. Efforts to compare and pool dMRI measures use meta- or mega- analytical techniques to compensate for these sources of variance. Meta-analytical methods gauge the consistency of effects, and mega-analytical methods involve mathematical or statistical transformations of the data. Here, we review some recent advances that allowed the diffusion community to create large scale population studies with greater rigor and generalizability than was previously attainable by individual studies.

关键词： Multi-site Harmonization diffusion MRI DTI DWI

来源：评论

学校读者我要写书评

暂无评论

Improving Graph-Based Tractography Plausibility Using Microstructure Information

Improving Graph-Based Tractography Plausibility Using Micros...

引用

作者： Battocchio, Matteo Girard, Gabriel Barakovic, Muhamed Ocampo, Mario Thiran, Jean-Philippe Schiavi, Simona Daducci, Alessandro Univ Verona Comp Sci Dept Verona Italy Ecole Polytech Fed Lausanne Signal Proc Lab LTS5 Lausanne Switzerland Univ Hosp Ctr CHUV Dept Radiol Lausanne Switzerland Univ Lausanne UNIL Lausanne Switzerland

ISBN: (纸本)9783030058319;9783030058302

Tractography is a unique tool to study neurological disorders for its ability to infer the major neural tracts from diffusion MRI data, thus allowing the investigation of the connectivity of the brain in-vivo. Tractography has seen a remarkable interest over the years and a large number of algorithms have been proposed. The choice of which method to use in a given application is usually a trade-off between its computational complexity and the quality of the reconstructions. So-called "shortest path " methods represent an interesting option, as they are computationally efficient, robust to noise and their formulation is very flexible. However, they also come with limitations. For instance, the reconstructed streamlines tend to be collapsed and to share part of their path, especially in regions with highly curved fiber bundles. This can introduce voxels with incorrectly high or low streamline density, which does not correspond to the underlying fiber geometry. To mitigate this problem, we propose an iterative procedure that uses microstructure information and provides feedback to the shortest path tractography algorithm about the plausibility of the reconstructions. We evaluated our method on a synthetic phantom and show that the spatial distribution of streamlines is in closer agreement with the ground truth.

关键词： Diffusion MRI Tractography Graph model Shortest path Microstructure informed tractography Brain connectivity

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共26页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：