<b>VISION — an open-source software for automated multi-dimensional image analysis of cellular biophysics</b>

It contains data sets from Weber et al, Journal of Cell Science, 2024 (https://doi.org/10.1242/jcs.262166)
The details for citation provided in the README file.
Please cite this item as:
Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A. Andronico
DOI: 10.17044/scilifelab.26233184
It contains microscopy images and excel sheets of the data.
<strong>Abstract</strong>: Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Python for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption.
<strong>Data usage</strong>
Researchers are welcome to use the data contained in the dataset for any projects. Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License.
<strong>Data Content</strong>
lsm or czi files for confocal and spectral images
tif files for super-resolution images
Excel files for graphs
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<strong>Software to open files</strong>
.xlsx - Microsoft Excel
.tif, .lsm, .czi - Fiji (https://imagej.net/software/fiji/)

本数据集包含Weber等人2024年发表于《Journal of Cell Science》的相关数据集（https://doi.org/10.1242/jcs.262166），引用详情请参见README文件。
请按以下方式引用本数据集：
Florian Weber, Sofiia Iskrak, Franziska Ragaller, Jan Schlegel, Birgit Plochberger, Erdinc Sezgin, Luca A. Andronico
DOI: 10.17044/scilifelab.26233184
本数据集包含实验显微图像与数据Excel表格。
<strong>摘要</strong>：环境敏感性探针常被应用于光谱/多通道显微成像技术，以研究细胞稳态的变化。然而，当前可用于处理光谱图像的开源软件包数量稀少且功能范围受限。本文介绍了VISION——一款基于Python开发的独立光谱分析软件，其适用性得到了显著提升。除经典的基于强度的分析外，该软件支持批量处理多维图像，具备先进的单细胞分割功能，还可对光谱执行用户自定义的数学运算，以计算单细胞的生物物理与代谢参数。VISION可实现膜流动性、线粒体膜电位等属性的三维与时空映射。我们通过将VISION应用于多项研究，验证了其广泛适用性：包括探究多种药物对细胞生物物理特性的影响、膜流动性与线粒体膜电位的相关性、细胞间接触区域的蛋白质分布，以及细胞衍生囊泡中的纳米结构域特性。随软件代码一同提供的还有图形用户界面，便于用户快速上手使用。
<strong>数据使用</strong>
欢迎研究人员将本数据集包含的数据用于各类科研项目。若使用本数据集或基于其发表成果，请引用本数据集。我们鼓励按照CC BY 4.0协议进行复用。
<strong>数据内容</strong>
共聚焦及光谱成像文件：lsm或czi格式
超分辨率成像文件：tif格式
图表数据文件：Excel表格
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<strong>文件打开软件</strong>
.xlsx格式文件：Microsoft Excel
.tif、.lsm、.czi格式文件：Fiji（https://imagej.net/software/fiji/）