Fluorender: An Imaging Tool for Visualization and Analysis of Confocal Data as Ap

Fluorender:用于共焦数据可视化和分析的成像工具

基本信息

  • 批准号:
    8333341
  • 负责人:
  • 金额:
    $ 31.4万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-20 至 2015-05-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The zebrafish offers unique advantages as a vertebrate system to analyze cell and tissue structure and development in vivo. External fertilization and transparent larvae allow imaging of cells in live, developing animals. New genetic techniques can knock out most zebrafish genes, making it critical to develop high- throughput techniques to analyze mutant phenotypes (the "phenome project"). For all these experiments, confocal microscopy is an essential tool, making it equally critical to develop software to analyze 3D and 4D (3D over time) confocal data and quickly derive biologically-relevant conclusions, both qualitative and quantitative. Image analysis requires five steps: preprocessing, registration, visualization, segmentation, and quantitation. We have already developed a downloadable confocal analysis application, FluoRender, and optimized it for visualization, providing significant advantages over existing commercial applications. The present proposal would make FluoRender a full-featured package by adding the other four steps. Our goal is to enable the biologist to easily analyze 3D and 4D confocal data, identifying and measuring features of interest, and allowing rapid repetitive analysis of multiple samples. For features like segmentation that benefit from automation, we provide user validation and editing, emphasizing high accuracy rather than pure speed. We will focus on three specific problems: 1) 3D image mosaicking, 4D drift removal; 2) 3D segmentation of confocal data; and 3) 4D tracking in confocal data. Mosaicking allows scanning of specimens larger than a microscope's field of view. Timelapse experiments benefit from 4D drift removal, since the growing embryo can change shape or the microscope's focus can drift. We will develop segmentation methods for objects from three classes: nuclei/cells, axons/dendrites, and tissues. We will develop semi-automatic segmentation methods for zebrafish labeled with multiple fluorophores, or spectrally (Brainbow). We will develop methods so that once cells or tissues are initially segmented, they can be tracked over time, then visualized co-registered with the raw data, providing context for interpreting their motion. The improved FluoRender software will provide a freely-distributed, portable suite that enables rapid analysis of 3D or 4D confocal datasets. This will aid in analyzing cell movements, neuronal circuitry, and tissue development in wildtype and mutant embryos. Given the growing relevance of zebrafish as a human disease model, the proposed analysis software can be expected to benefit our understanding of many different developmental, neurobiological, and metabolic diseases.
描述(由申请人提供):斑马鱼作为脊椎动物系统提供了独特的优势来分析体内细胞和组织结构以及发育。外部受精和透明的幼虫允许活的、发育中的动物的细胞成像。新的遗传技术可以敲除大多数斑马鱼基因,这使得开发高通量技术来分析突变表型(“表型组项目”)至关重要。对于所有这些实验,共聚焦显微镜是一个必不可少的工具,因此开发软件来分析3D和4D(随时间变化的3D)共聚焦数据并快速得出生物相关的定性和定量结论同样重要。图像分析需要五个步骤:预处理,配准,可视化,分割和定量。我们已经开发了一个可下载的共聚焦分析应用程序FluoRender,并对其进行了可视化优化,与现有的商业应用程序相比具有显着的优势。本提案将通过添加其他四个步骤使FluoRender成为一个功能齐全的软件包。 我们的目标是使生物学家能够轻松分析3D和4D共聚焦数据,识别和测量感兴趣的特征,并允许快速重复分析多个样品。对于像分割这样受益于自动化的功能,我们提供用户验证和编辑,强调高准确性而不是纯粹的速度。我们将重点讨论三个具体问题:1)3D图像拼接,4D漂移去除; 2)共焦数据的3D分割; 3)共焦数据中的4D跟踪。镶嵌允许扫描大于显微镜视野的标本。延时实验受益于4D漂移消除,因为生长的胚胎可以改变形状或显微镜的焦点可以漂移。我们将开发三个类别的对象分割方法:细胞核/细胞,轴突/树突和组织。我们将开发标记有多个荧光团或光谱(Brainbow)的斑马鱼的半自动分割方法。我们将开发方法,以便一旦细胞或组织最初被分割,它们就可以随着时间的推移被跟踪,然后与原始数据进行可视化配准,为解释它们的运动提供背景。 改进后的FluoRender软件将提供一个免费分发的便携式套件,可以快速分析3D或4D共聚焦数据集。这将有助于分析野生型和突变型胚胎中的细胞运动、神经元回路和组织发育。考虑到斑马鱼作为人类疾病模型的相关性越来越大,预计所提出的分析软件将有助于我们了解许多不同的发育,神经生物学和代谢疾病。

项目成果

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Charles Hansen其他文献

Charles Hansen的其他文献

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{{ truncateString('Charles Hansen', 18)}}的其他基金

FluoRender: Rapid Quantitative Analysis and Adaptive Workflows for Fluorescence Microscopy Data in Fundamental Biomedical Research
FluoRender:基础生物医学研究中荧光显微镜数据的快速定量分析和自适应工作流程
  • 批准号:
    10276704
  • 财政年份:
    2021
  • 资助金额:
    $ 31.4万
  • 项目类别:
FluoRender: Visualization-Based and Interactive Analysis for Multichannel Microscopy Data
FluoRender:多通道显微镜数据的基于可视化和交互式分析
  • 批准号:
    9916753
  • 财政年份:
    2017
  • 资助金额:
    $ 31.4万
  • 项目类别:
Fluorender: An Imaging Tool for Visualization and Analysis of Confocal Data as Ap
Fluorender:用于共焦数据可视化和分析的成像工具
  • 批准号:
    8145953
  • 财政年份:
    2011
  • 资助金额:
    $ 31.4万
  • 项目类别:
Fluorender: An Imaging Tool for Visualization and Analysis of Confocal Data as Ap
Fluorender:用于共焦数据可视化和分析的成像工具
  • 批准号:
    8477216
  • 财政年份:
    2011
  • 资助金额:
    $ 31.4万
  • 项目类别:

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