FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis.
FLIMJ: An open-source ImageJ toolkit for fluorescence lifetime image data analysis.
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DOI：
10.1371/journal.pone.0238327
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发表时间：
2020
期刊：
影响因子：
3.7
通讯作者：
Eliceiri KW
中科院分区：
文献类型：
--
作者：
Gao D;Barber PR;Chacko JV;Kader Sagar MA;Rueden CT;Grislis AR;Hiner MC;Eliceiri KW
在荧光显微镜领域，对能够利用图像每个像素的完整信息的动态技术的需求持续存在。一种已被证明有能力从荧光成像中获得额外信息的成像技术是荧光寿命成像显微镜(FLIM)。FLiM可以测量荧光团处于激发能态的时间，这种测量受到其化学微环境变化的影响，例如与其他荧光团的接近程度、pH值和疏水性区域。这种提供微环境信息的能力使FLIM成为细胞成像研究的强大工具，范围从新陈代谢测量到蛋白质之间的距离测量。由于越来越多地使用FLIM，因此有必要开发将FLIM分析与图像和数据处理相结合的计算工具。为了满足这一需求，我们创建了FLIMJ，这是一个ImageJ插件和工具包，允许轻松使用和开发具有胶片数据的可扩展图像分析工作流。建立在FLIMLib衰变曲线拟合库和ImageJ Ops框架之上，FLIMJ提供与许多其他ImageJ组件无缝集成的薄膜拟合例程，并能够扩展以创建复杂的薄膜分析工作流。基于ImageJ Ops的构建还使FLIMJ的例程能够与Jupyter笔记本电脑一起使用，并与Python和Groovy等科学友好型编程自然集成。我们在两个分析场景中展示了FLIMJ的可扩展性：基于生命周期的图像分割和图像共定位。我们还通过将它们与行业薄膜分析标准进行比较来验证拟合程序。
In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state, and this measurement is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with many other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJ’s routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing them against industry FLIM analysis standards.
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DOI：
10.1083/jcb.201004104
发表时间：
2010-05-31
期刊：
The Journal of cell biology
影响因子：
--
作者：
Linkert M;Rueden CT;Allan C;Burel JM;Moore W;Patterson A;Loranger B;Moore J;Neves C;Macdonald D;Tarkowska A;Sticco C;Hill E;Rossner M;Eliceiri KW;Swedlow JR
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影响因子：
5.8
作者：
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通讯作者：
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影响因子：
3.2
作者：
Chacko, Jenu V.;Eliceiri, Kevin W.
通讯作者：
Eliceiri, Kevin W.
DOI：
10.1074/jbc.m111.331967
发表时间：
2012-05-18
期刊：
The Journal of biological chemistry
影响因子：
--
作者：
Hunt J;Keeble AH;Dale RE;Corbett MK;Beavil RL;Levitt J;Swann MJ;Suhling K;Ameer-Beg S;Sutton BJ;Beavil AJ
通讯作者：
Beavil AJ