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ABI Innovation: Towards the Neurome -- Automated Image Analysis for Neuroinformatics

ABI Innovation: Towards the Neurome -- Automated Image Analysis for Neuroinformatics
ABI 创新:迈向神经元——神经信息学自动图像分析
批准号:
1062433
负责人:
Scott Acton
金额:
$48.35万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-05-01 至 2016-04-30

项目摘要

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中文摘要
翻译
一个令人兴奋和新兴的生物研究领域集中在神经元图谱的创建上,通常被称为神经组,它提供了特定生物体中所有神经元的结构描述。除了繁琐的人工分析之外,目前还没有可靠的方法从3D图像中提取有关神经元的结构知识。该项目将开发全自动信息学工具,使生物学家能够从图像中自动提取3D结构。Tree2Tree算法将神经元树的3D图像转换为图论树,这些图论树可以被计算机有效地表示并进行比较,从而能够检索和传播有关生物体神经系统的结构信息。Tree2Tree以提取神经元的管状结构、执行神经突起部分的连接成分分析、将神经元表示为图论树、修剪树以及在神经元数据库中比较结果树等新技术为特色。一个来自生物学和工程学的跨学科团队已经成立,以解决创建神经元图谱的研究问题。软件方面的创新将为创建复杂生物体的新地图集打开大门,这些地图集反过来可用于重要的发育和行为研究。这些信息学工具将作为促进生物发现的平台。所有拟议的信息学工具都将作为开放源代码和插件在三个广泛使用的存储库以及http://viva.ee.virginia.edu/research.html上传播。这项研究的最终成果将包括信息学工具以及使用果蝇的工作数据库示例。
英文摘要
An exciting and emerging area of biological research is centered on the creation of neuronal atlases, often referred to as neuromes, which provide structural description of all neurons in a particular organism. Aside from tedious manual analysis, there exist no reliable methods to extract structural knowledge regarding a neuron from a 3D image. This project will develop fully automated informatics tools that will allow the biologist to automatically extract 3D structure from the images. The Tree2Tree algorithm converts 3D images of neuronal trees to graph theoretic trees that can be represented efficiently by computers and compared to enable retrieval and dissemination of structural information regarding an organism's neurome. Tree2Tree features novel techniques for extracting the tubular structure of the neurons, for performing connected component analysis of the neurite portions, for representing the neuron as a graph theoretic tree, for pruning the tree and for comparing the resultant trees in a database of neurons.A cross-disciplinary team from Biology and Engineering has been assembled to tackle the research problem of creating a neuronal atlas. The innovations in software will open doors to creating new atlases for complex organisms, which can be in turn used in important developmental and behavioral studies. These informatics tools will serve as a platform from which advances in biological discovery can occur. All proposed informatics tools will be disseminated as open source code and plug-ins in three widely used repositories as well as at http://viva.ee.virginia.edu/research.html. The final product of this research will include informatics tools as well as a working database example using the fruit fly.
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EAGER: Spatiotemporal Transformer for Activity Recognition
  • 批准号:
    2322993
  • 项目类别:
    Standard Grant
  • 资助金额:
    $28.08万
  • 财政年份:
    2023
  • 负责人:
    Scott Acton
  • 依托单位:
Intergovernmental Personnel Act Assignment
  • 批准号:
    1950730
  • 项目类别:
    Intergovernmental Personnel Award
  • 资助金额:
    $26.47万
  • 财政年份:
    2019
  • 负责人:
    Scott Acton
  • 依托单位:
Decentralized Image Retrieval for Education (DIRECT)
  • 批准号:
    0121596
  • 项目类别:
    Standard Grant
  • 资助金额:
    $49.44万
  • 财政年份:
    2002
  • 负责人:
    Scott Acton
  • 依托单位:
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