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Topological Subdivision Graphs for Comparative and Multifield Visualization 用于比较和多场可视化的拓扑细分图
Mathematics and visualization
Pub Date : 2020-01-01 DOI: 10.1007/978-3-030-43036-8_13
Christian Heine, C. Garth
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引用次数: 0
Magnetic Resonance Assessment of Effective Confinement Anisotropy with Orientationally-Averaged Single and Double Diffusion Encoding 定向平均单扩散和双扩散编码有效约束各向异性的磁共振评价
Mathematics and visualization
Pub Date : 2019-12-30 DOI: 10.1007/978-3-030-56215-1_10
Cem Yolcu, M. Herberthson, C. Westin, E. Ozarslan
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引用次数: 4
Persistence Concepts for 2D Skeleton Evolution Analysis 二维骨骼进化分析的持久性概念
Mathematics and visualization
Pub Date : 2019-07-31 DOI: 10.1007/978-3-030-43036-8_9
Bastian Alexander Rieck, F. Sadlo, H. Leitte
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引用次数: 3
Hierarchies and Ranks for Persistence Pairs 持久性对的层次结构和秩
Mathematics and visualization
Pub Date : 2019-07-31 DOI: 10.1007/978-3-030-43036-8_1
Bastian Alexander Rieck, F. Sadlo, H. Leitte
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引用次数: 9
An Overview of the Topology ToolKit 拓扑工具包概述
Mathematics and visualization
Pub Date : 2019-06-17 DOI: 10.1007/978-3-030-83500-2_16
Talha Bin Masood, J. Budin, M. Falk, Guillaume Favelier, C. Garth, Charles Gueunet, P. Guillou, L. Hofmann, P. Hristov, Adhitya Kamakshidasan, Christopher P. Kappe, Pavol Klacansky, Patrick Laurin, J. Levine, Jonas Lukasczyk, Daisuke Sakurai, Maxime Soler, P. Steneteg, Julien Tierny, W. Usher, Jules Vidal, Michal Wozniak
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引用次数: 25
Computational Diffusion MRI 计算扩散MRI
Mathematics and visualization
Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-05831-9
Noemi G. Gyori, J. Hutter, V. Nath, M. Palombo, M. Pizzolato
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引用次数: 0
Topological Data Analysis for Scientific Visualization 用于科学可视化的拓扑数据分析
Mathematics and visualization
Pub Date : 2018-01-29 DOI: 10.1007/978-3-319-71507-0
Julien Tierny
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引用次数: 28
Pathological and Test Cases for Reeb Analysis Reeb分析的病理和测试案例
Mathematics and visualization
Pub Date : 2017-02-27 DOI: 10.1007/978-3-030-43036-8_7
H. Carr, Julien Tierny, G. Weber
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引用次数: 6
Flexible Fiber Surfaces: A Reeb-Free Approach 柔性纤维表面:一种无簧片的方法
Mathematics and visualization
Pub Date : 2017-02-27 DOI: 10.1007/978-3-030-43036-8_12
Daisuke Sakurai, K. Ono, H. Carr, J. Nonaka, T. Kawanabe
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引用次数: 5
Rich club network analysis shows distinct patterns of disruption in frontotemporal dementia and Alzheimer's disease. 丰富的俱乐部网络分析显示，额颞叶痴呆和阿尔茨海默病的破坏模式不同。
Mathematics and visualization
Pub Date : 2014-01-01 DOI: 10.1007/978-3-319-11182-7_2
Madelaine Daianu, Neda Jahanshad, Julio E Villalon-Reina, Mario F Mendez, George Bartzokis, Elvira E Jimenez, Aditi Joshi, Joseph Barsuglia, Paul M Thompson

Diffusion imaging and brain connectivity analyses can reveal the underlying organizational patterns of the human brain, described as complex networks of densely interlinked regions. Here, we analyzed 1.5-Tesla whole-brain diffusion-weighted images from 64 participants - 15 patients with behavioral variant frontotemporal (bvFTD) dementia, 19 with early-onset Alzheimer's disease (EOAD), and 30 healthy elderly controls. Based on whole-brain tractography, we reconstructed structural brain connectivity networks to map connections between cortical regions. We examined how bvFTD and EOAD disrupt the weighted 'rich club' - a network property where high-degree network nodes are more interconnected than expected by chance. bvFTD disrupts both the nodal and global organization of the network in both low- and high-degree regions of the brain. EOAD targets the global connectivity of the brain, mainly affecting the fiber density of high-degree (highly connected) regions that form the rich club network. These rich club analyses suggest distinct patterns of disruptions among different forms of dementia.

扩散成像和大脑连接分析可以揭示人类大脑的潜在组织模式，被描述为密集互连区域的复杂网络。在这里，我们分析了64名参与者的1.5特斯拉全脑扩散加权图像——15名行为变异额颞叶痴呆患者、19名早发性阿尔茨海默病患者和30名健康老年对照。在全脑束成像的基础上，我们重建了大脑结构连接网络，以绘制皮层区域之间的连接。我们研究了bvFTD和EOAD是如何破坏加权的“富裕俱乐部”的——这是一种网络特性，其中高度网络节点的互联程度比预期的要高。bvFTD破坏了大脑低度和高度区域网络的节点和全局组织。EOAD的目标是大脑的全球连通性，主要影响形成丰富俱乐部网络的高度（高度连通）区域的纤维密度。这些丰富的俱乐部分析表明，不同形式的痴呆症之间存在不同的干扰模式。
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引用次数: 10
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