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: University of Virginia Main Campus
• 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
• 起止时间: 2011-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1062433&HistoricalAwards=false
• 关键词: ABI; Innovation; Towards; Neurome; Automated

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.

一个令人兴奋的新兴生物学研究领域集中在创建神经元图谱，通常被称为神经图谱，它提供了对特定有机体中所有神经元的结构描述。除了繁琐的人工分析之外，还没有可靠的方法来从3D图像中提取关于神经元的结构知识。该项目将开发全自动信息学工具，使生物学家能够自动从图像中提取3D结构。Tree2Tree算法将神经树的3D图像转换为图论树，计算机可以有效地表示这些树，并进行比较，以检索和传播有关有机体神经酶的结构信息。Tree2Tree采用了新的技术来提取神经元的管状结构，执行轴突部分的连通成分分析，将神经元表示为图论树，修剪树，并在神经元数据库中比较结果树。来自生物和工程的一个跨学科团队已经聚集在一起，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图谱打开大门，这些图谱反过来可以用于重要的发育和行为研究。这些信息学工具将作为一个平台，在生物发现方面取得进展。所有拟议的信息学工具将作为开放源代码和插件在三个广泛使用的存储库中以及在http://viva.ee.virginia.edu/research.html.上分发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。