• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

使用多向各向异性符号样本通过LIC映射进行纤维可视化

Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples.

作者信息

Höller Mark, Otto Kay-M, Klose Uwe, Groeschel Samuel, Ehricke Hans-H

机构信息

Institute for Applied Computer Science (IACS), Stralsund University, Zur Schwedenschanze 15, 18435 Stralsund, Germany.

MR Research Group, Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Straße 3, 72076 Tübingen, Germany.

出版信息

Int J Biomed Imaging. 2014;2014:401819. doi: 10.1155/2014/401819. Epub 2014 Aug 28.

DOI:10.1155/2014/401819
PMID:25254038
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4164306/
Abstract

Line integral convolution (LIC) is used as a texture-based technique in computer graphics for flow field visualization. In diffusion tensor imaging (DTI), LIC bridges the gap between local approaches, for example directionally encoded fractional anisotropy mapping and techniques analyzing global relationships between brain regions, such as streamline tracking. In this paper an advancement of a previously published multikernel LIC approach for high angular resolution diffusion imaging visualization is proposed: a novel sampling scheme is developed to generate anisotropic glyph samples that can be used as an input pattern to the LIC algorithm. Multicylindrical glyph samples, derived from fiber orientation distribution (FOD) functions, are used, which provide a method for anisotropic packing along integrated fiber lines controlled by a uniform random algorithm. This allows two- and three-dimensional LIC maps to be generated, depicting fiber structures with excellent contrast, even in regions of crossing and branching fibers. Furthermore, a color-coding model for the fused visualization of slices from T1 datasets together with directionally encoded LIC maps is proposed. The methodology is evaluated by a simulation study with a synthetic dataset, representing crossing and bending fibers. In addition, results from in vivo studies with a healthy volunteer and a brain tumor patient are presented to demonstrate the method's practicality.

摘要

线积分卷积（LIC）在计算机图形学中作为一种基于纹理的技术用于流场可视化。在扩散张量成像（DTI）中，LIC弥合了局部方法（例如方向编码分数各向异性映射）与分析脑区之间全局关系的技术（如流线追踪）之间的差距。本文提出了一种先前发表的用于高角分辨率扩散成像可视化的多内核LIC方法的改进：开发了一种新颖的采样方案来生成各向异性的字形样本，这些样本可作为LIC算法的输入模式。使用从纤维取向分布（FOD）函数导出的多圆柱字形样本，它提供了一种沿着由均匀随机算法控制的整合纤维线进行各向异性堆积的方法。这使得能够生成二维和三维LIC图，即使在纤维交叉和分支区域也能以出色的对比度描绘纤维结构。此外，还提出了一种用于将T1数据集的切片与方向编码的LIC图进行融合可视化的颜色编码模型。通过对代表交叉和弯曲纤维的合成数据集进行模拟研究来评估该方法。此外，还展示了对一名健康志愿者和一名脑肿瘤患者进行体内研究的结果，以证明该方法的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3665f66271a2/IJBI2014-401819.015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/15b8f59ef4db/IJBI2014-401819.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3cd9b9084831/IJBI2014-401819.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/ab098b657e07/IJBI2014-401819.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/356e48326b8a/IJBI2014-401819.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/88b4c8d55533/IJBI2014-401819.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/2d2e496f83d5/IJBI2014-401819.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/c27a5ed120cc/IJBI2014-401819.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/1073701d2fcf/IJBI2014-401819.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/88f65b0c45f8/IJBI2014-401819.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/74889b70b1da/IJBI2014-401819.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3a45003ad74c/IJBI2014-401819.011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/8b2b4ba288cc/IJBI2014-401819.012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/457b8b2156a0/IJBI2014-401819.013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/d56bf84f1068/IJBI2014-401819.014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3665f66271a2/IJBI2014-401819.015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/15b8f59ef4db/IJBI2014-401819.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3cd9b9084831/IJBI2014-401819.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/ab098b657e07/IJBI2014-401819.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/356e48326b8a/IJBI2014-401819.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/88b4c8d55533/IJBI2014-401819.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/2d2e496f83d5/IJBI2014-401819.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/c27a5ed120cc/IJBI2014-401819.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/1073701d2fcf/IJBI2014-401819.008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/88f65b0c45f8/IJBI2014-401819.009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/74889b70b1da/IJBI2014-401819.010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3a45003ad74c/IJBI2014-401819.011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/8b2b4ba288cc/IJBI2014-401819.012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/457b8b2156a0/IJBI2014-401819.013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/d56bf84f1068/IJBI2014-401819.014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a810/4164306/3665f66271a2/IJBI2014-401819.015.jpg

相似文献

1
Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples.使用多向各向异性符号样本通过LIC映射进行纤维可视化
Int J Biomed Imaging. 2014;2014:401819. doi: 10.1155/2014/401819. Epub 2014 Aug 28.
2
Clinical Application of Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples (A-Glyph LIC).使用多方向各向异性符号样本（A形LIC）的LIC图进行纤维可视化的临床应用
Clin Neuroradiol. 2017 Sep;27(3):263-273. doi: 10.1007/s00062-015-0486-8. Epub 2015 Nov 27.
3
A localized Richardson-Lucy algorithm for fiber orientation estimation in high angular resolution diffusion imaging.一种用于高角分辨率扩散成像中纤维方向估计的局部理查森- Lucy算法。
Med Phys. 2015 May;42(5):2524-39. doi: 10.1118/1.4917082.
4
Anisotropic noise samples.各向异性噪声样本。
IEEE Trans Vis Comput Graph. 2008 Mar-Apr;14(2):342-54. doi: 10.1109/TVCG.2007.70434.
5
Visualization of mouse barrel cortex using ex-vivo track density imaging.使用离体轨迹密度成像技术对小鼠大脑皮层 barrels 区进行可视化。
Neuroimage. 2014 Feb 15;87:465-75. doi: 10.1016/j.neuroimage.2013.09.030. Epub 2013 Sep 21.
6
Output-sensitive 3D line integral convolution.输出敏感的三维线积分卷积
IEEE Trans Vis Comput Graph. 2008 Jul-Aug;14(4):820-34. doi: 10.1109/TVCG.2008.25.
7
Magnetic resonance imaging diffusion tensor tractography: evaluation of anatomic accuracy of different fiber tracking software packages.磁共振成像弥散张量纤维束示踪：不同纤维追踪软件包的解剖准确性评估。
World Neurosurg. 2014 Jan;81(1):144-50. doi: 10.1016/j.wneu.2013.01.004. Epub 2013 Jan 4.
8
Fused DTI/HARDI visualization.融合 DTI/HARDI 可视化。
IEEE Trans Vis Comput Graph. 2011 Oct;17(10):1407-19. doi: 10.1109/TVCG.2010.244.
9
Diffusion tensor visualization with glyph packing.
IEEE Trans Vis Comput Graph. 2006 Sep-Oct;12(5):1329-35. doi: 10.1109/tvcg.2006.134.
10
Animation of orthogonal texture patterns for vector field visualization.用于矢量场可视化的正交纹理图案动画。
IEEE Trans Vis Comput Graph. 2008 Jul-Aug;14(4):741-55. doi: 10.1109/TVCG.2008.36.

引用本文的文献

1
Fiber visualization for preoperative glioma assessment: Tractography versus local connectivity mapping.纤维可视化用于术前胶质瘤评估：示踪技术与局部连接图。
PLoS One. 2019 Dec 12;14(12):e0226153. doi: 10.1371/journal.pone.0226153. eCollection 2019.
2
Clinical Application of Fiber Visualization with LIC Maps Using Multidirectional Anisotropic Glyph Samples (A-Glyph LIC).使用多方向各向异性符号样本（A形LIC）的LIC图进行纤维可视化的临床应用
Clin Neuroradiol. 2017 Sep;27(3):263-273. doi: 10.1007/s00062-015-0486-8. Epub 2015 Nov 27.

本文引用的文献

1
White matter fiber tractography: why we need to move beyond DTI.白质纤维束追踪：为什么我们需要超越 DTI。
J Neurosurg. 2013 Jun;118(6):1367-77. doi: 10.3171/2013.2.JNS121294. Epub 2013 Mar 29.
2
White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI.白质完整性、纤维数量及其他谬论：弥散磁共振成像的注意事项。
Neuroimage. 2013 Jun;73:239-54. doi: 10.1016/j.neuroimage.2012.06.081. Epub 2012 Jul 23.
3
Angular smoothing and radial regularization of ODF fields: application on deterministic crossing fiber tractography.
各向异性平滑和 ODF 场的径向正则化：在确定性跨纤维束追踪中的应用。
Phys Med. 2013 Jan;29(1):17-32. doi: 10.1016/j.ejmp.2011.10.002. Epub 2011 Nov 2.
4
Regularization of bending and crossing white matter fibers in MRI Q-ball fields.磁共振 Q 球成像中白质纤维弯曲和交叉的正则化。
Magn Reson Imaging. 2011 Sep;29(7):916-26. doi: 10.1016/j.mri.2011.05.002. Epub 2011 Jun 25.
5
Track-density imaging (TDI): super-resolution white matter imaging using whole-brain track-density mapping.轨迹密度成像（TDI）：使用全脑轨迹密度图进行超高分辨率白质成像。
Neuroimage. 2010 Dec;53(4):1233-43. doi: 10.1016/j.neuroimage.2010.07.024. Epub 2010 Jul 17.
6
Reconstruction of the orientation distribution function in single- and multiple-shell q-ball imaging within constant solid angle.在恒定立体角内进行单壳和多壳 q-球成像中的方位分布函数重建。
Magn Reson Med. 2010 Aug;64(2):554-66. doi: 10.1002/mrm.22365.
7
Direct visualization of fiber information by coherence.相干直接可视化纤维信息。
Int J Comput Assist Radiol Surg. 2010 Mar;5(2):125-31. doi: 10.1007/s11548-009-0302-5. Epub 2009 Apr 15.
8
Isosurface-based generation of hulls encompassing neuronal pathways.基于等值面生成包含神经通路的外壳。
Stereotact Funct Neurosurg. 2009;87(1):50-60. doi: 10.1159/000195720. Epub 2009 Jan 28.
9
Estimating crossing fibers: a tensor decomposition approach.估计交叉纤维：一种张量分解方法。
IEEE Trans Vis Comput Graph. 2008 Nov-Dec;14(6):1635-42. doi: 10.1109/TVCG.2008.128.
10
Anisotropic noise samples.各向异性噪声样本。
IEEE Trans Vis Comput Graph. 2008 Mar-Apr;14(2):342-54. doi: 10.1109/TVCG.2007.70434.