• 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

大神经影像学数据集在阿尔茨海默病中的临床价值。

The clinical value of large neuroimaging data sets in Alzheimer's disease.

机构信息

Laboratory of Neuro Imaging, Department of Neurology, David Geffen School of Medicine at UCLA, 635 Charles Young Drive S, Suite 225, Los Angeles, CA 90095-7334, USA.

出版信息

Neuroimaging Clin N Am. 2012 Feb;22(1):107-18, ix. doi: 10.1016/j.nic.2011.11.008. Epub 2011 Dec 17.

DOI:10.1016/j.nic.2011.11.008
PMID:22284737
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3555557/
Abstract

Rapid advances in neuroimaging and cyberinfrastructure technologies have brought explosive growth in the Web-based warehousing, availability, and accessibility of imaging data on a variety of neurodegenerative and neuropsychiatric disorders and conditions. There has been a prolific development and emergence of complex computational infrastructures that serve as repositories of databases and provide critical functionalities such as sophisticated image analysis algorithm pipelines and powerful three-dimensional visualization and statistical tools. The statistical and operational advantages of collaborative, distributed team science in the form of multisite consortia push this approach in a diverse range of population-based investigations.

摘要

神经影像学和网络基础设施技术的快速发展,使得基于网络的各种神经退行性和神经精神疾病及病症的成像数据仓储、可用性和可及性呈爆炸式增长。大量复杂的计算基础设施已经开发和出现,它们充当数据库存储库,并提供关键功能,如复杂的图像分析算法管道以及强大的三维可视化和统计工具。以多站点联盟形式的协作式、分布式团队科学的统计和操作优势,推动了这种方法在各种基于人群的研究中的应用。

相似文献

1
The clinical value of large neuroimaging data sets in Alzheimer's disease.大神经影像学数据集在阿尔茨海默病中的临床价值。
Neuroimaging Clin N Am. 2012 Feb;22(1):107-18, ix. doi: 10.1016/j.nic.2011.11.008. Epub 2011 Dec 17.
2
Graphical neuroimaging informatics: application to Alzheimer's disease.图形神经影像学信息学:在阿尔茨海默病中的应用。
Brain Imaging Behav. 2014 Jun;8(2):300-10. doi: 10.1007/s11682-013-9273-9.
3
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.脑成像数据结构(BIDS)应用程序:提高神经成像数据分析方法的易用性、可及性和可重复性。
PLoS Comput Biol. 2017 Mar 9;13(3):e1005209. doi: 10.1371/journal.pcbi.1005209. eCollection 2017 Mar.
4
Design of a Graph-Based System for Similar Case Retrieval of Pulmonary Nodules.基于图的肺结节相似病例检索系统设计
Stud Health Technol Inform. 2015;216:1079.
5
Texture analysis software: integration with a radiological workstation.纹理分析软件:与放射工作站的集成
Stud Health Technol Inform. 2012;180:1030-4.
6
Virtual imaging laboratories for marker discovery in neurodegenerative diseases.用于神经退行性疾病标志物发现的虚拟成像实验室。
Nat Rev Neurol. 2011 Jul 5;7(8):429-38. doi: 10.1038/nrneurol.2011.99.
7
VIEWDEX: A STATUS REPORT.视图索引:一份状态报告。
Radiat Prot Dosimetry. 2016 Jun;169(1-4):38-45. doi: 10.1093/rpd/ncv543. Epub 2016 Jan 27.
8
V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets.V3D 能够实时可视化和定量分析大规模生物图像数据集。
Nat Biotechnol. 2010 Apr;28(4):348-53. doi: 10.1038/nbt.1612. Epub 2010 Mar 14.
9
A recommender system for medical imaging diagnostic.一种用于医学影像诊断的推荐系统。
Stud Health Technol Inform. 2015;210:461-3.
10
Requirements for optimum use of advanced image visualization tools.优化使用先进图像可视化工具的要求。
J Am Coll Radiol. 2007 Aug;4(8):525-6. doi: 10.1016/j.jacr.2007.05.011.

引用本文的文献

1
Open access image repositories: high-quality data to enable machine learning research.开放获取图像知识库:高质量数据,助力机器学习研究。
Clin Radiol. 2020 Jan;75(1):7-12. doi: 10.1016/j.crad.2019.04.002. Epub 2019 Apr 28.
2
National Neuroinformatics Framework for Canadian Consortium on Neurodegeneration in Aging (CCNA).加拿大衰老神经退行性变联盟(CCNA)的国家神经信息学框架。
Front Neuroinform. 2018 Dec 21;12:85. doi: 10.3389/fninf.2018.00085. eCollection 2018.
3
An Assessment of Imaging Informatics for Precision Medicine in Cancer.癌症精准医学中的影像信息学评估
Yearb Med Inform. 2017 Aug;26(1):110-119. doi: 10.15265/IY-2017-041. Epub 2017 Sep 11.
4
What can imaging tell us about cognitive impairment and dementia?影像学能告诉我们关于认知障碍和痴呆的哪些信息?
World J Radiol. 2016 Mar 28;8(3):240-54. doi: 10.4329/wjr.v8.i3.240.
5
Sharing big biomedical data.共享大型生物医学数据。
J Big Data. 2015;2. doi: 10.1186/s40537-015-0016-1. Epub 2015 Jun 27.
6
The Global Alzheimer's Association Interactive Network.全球阿尔茨海默病协会互动网络
Alzheimers Dement. 2016 Jan;12(1):49-54. doi: 10.1016/j.jalz.2015.06.1896. Epub 2015 Aug 28.
7
The Alzheimer's Disease Neuroimaging Initiative informatics core: A decade in review.阿尔茨海默病神经影像倡议信息学核心:十年回顾
Alzheimers Dement. 2015 Jul;11(7):832-9. doi: 10.1016/j.jalz.2015.04.004.
8
Big data and clinicians: a review on the state of the science.大数据与临床医生:科学现状综述。
JMIR Med Inform. 2014 Jan 17;2(1):e1. doi: 10.2196/medinform.2913.
9
Grey-matter volume as a potential feature for the classification of Alzheimer's disease and mild cognitive impairment: an exploratory study.灰质体积作为阿尔茨海默病和轻度认知障碍分类的潜在特征:一项探索性研究。
Neurosci Bull. 2014 Jun;30(3):477-89. doi: 10.1007/s12264-013-1432-x. Epub 2014 Apr 23.
10
Biomedical imaging informatics in the era of precision medicine: progress, challenges, and opportunities.精准医学时代的生物医学成像信息学:进展、挑战与机遇。
J Am Med Inform Assoc. 2013 Nov-Dec;20(6):1010-3. doi: 10.1136/amiajnl-2013-002315.

本文引用的文献

1
Functional network disruption in the degenerative dementias.退行性痴呆症的功能网络破坏。
Lancet Neurol. 2011 Sep;10(9):829-43. doi: 10.1016/S1474-4422(11)70158-2. Epub 2011 Jul 21.
2
AddNeuroMed and ADNI: similar patterns of Alzheimer's atrophy and automated MRI classification accuracy in Europe and North America.AddNeuroMed 和 ADNI:欧洲和北美的阿尔茨海默病萎缩模式相似,以及自动 MRI 分类准确性。
Neuroimage. 2011 Oct 1;58(3):818-28. doi: 10.1016/j.neuroimage.2011.06.065. Epub 2011 Jul 1.
3
Virtual imaging laboratories for marker discovery in neurodegenerative diseases.用于神经退行性疾病标志物发现的虚拟成像实验室。
Nat Rev Neurol. 2011 Jul 5;7(8):429-38. doi: 10.1038/nrneurol.2011.99.
4
Decoding continuous variables from neuroimaging data: basic and clinical applications.从神经影像数据中解码连续变量:基础与临床应用
Front Neurosci. 2011 Jun 15;5:75. doi: 10.3389/fnins.2011.00075. eCollection 2011.
5
Staging Alzheimer's disease progression with multimodality neuroimaging.用多模态神经影像学对阿尔茨海默病进展进行分期。
Prog Neurobiol. 2011 Dec;95(4):535-46. doi: 10.1016/j.pneurobio.2011.06.004. Epub 2011 Jun 22.
6
Neuroimaging markers for the prediction and early diagnosis of Alzheimer's disease dementia.用于预测和早期诊断阿尔茨海默病痴呆的神经影像学标志物。
Trends Neurosci. 2011 Aug;34(8):430-42. doi: 10.1016/j.tins.2011.05.005. Epub 2011 Jun 21.
7
Neuroimaging as endpoints in clinical trials: are we there yet? Perspective from the first Provence workshop.神经影像学作为临床试验的终点指标:我们做到了吗?来自普罗旺斯首次研讨会的观点。
Mol Psychiatry. 2011 Nov;16(11):1064-6. doi: 10.1038/mp.2011.62. Epub 2011 May 31.
8
The dynamic marker hypothesis of Alzheimer's disease and its implications for clinical imaging.阿尔茨海默病的动态标志物假说及其对临床成像的意义。
Q J Nucl Med Mol Imaging. 2011 Jun;55(3):237-49.
9
The human connectome: a complex network.人类连接组:一个复杂的网络。
Ann N Y Acad Sci. 2011 Apr;1224:109-125. doi: 10.1111/j.1749-6632.2010.05888.x. Epub 2011 Jan 4.
10
Multimodal classification of Alzheimer's disease and mild cognitive impairment.阿尔茨海默病和轻度认知障碍的多模态分类。
Neuroimage. 2011 Apr 1;55(3):856-67. doi: 10.1016/j.neuroimage.2011.01.008. Epub 2011 Jan 12.