MiCellAnnGELo: annotate microscopy time series of complex cell surfaces with 3D virtual reality.

MiCellAnnGELo: annotate microscopy time series of complex cell surfaces with 3D virtual reality.
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DOI:
10.1093/bioinformatics/btad013
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发表时间:
2023-01-01
期刊:
Bioinformatics (Oxford, England)
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3D活细胞显微镜的进步使人们能够高分辨率地捕捉以前未观察到的过程。然而,释放现代机器学习方法的力量以充分受益于这些技术,却因手动注释3D训练数据的困难而受挫。MiCellAnnGELo虚拟现实软件提供了一个身临其境的环境,用于查看和与4D显微镜数据进行交互,包括高效的注释工具。我们目前的工具标记细胞表面的广泛应用,包括细胞运动,胞吞和跨膜信号。MiCellAnnGELo采用跨平台(Mac/Unix/Windows)Unity游戏引擎,可在MIT许可下在https://github.com/CellDynamics/MiCellAnnGELo.git上获得,以及示例数据。MiCellAnnGELo可以在2D屏幕上以桌面模式运行,也可以使用带有兼容GPU的标准VR头显以3D模式运行。 补充数据可在Bioinformatics在线获得。
Advances in 3D live cell microscopy are enabling high-resolution capture of previously unobserved processes. Unleashing the power of modern machine learning methods to fully benefit from these technologies is, however, frustrated by the difficulty of manually annotating 3D training data. MiCellAnnGELo virtual reality software offers an immersive environment for viewing and interacting with 4D microscopy data, including efficient tools for annotation. We present tools for labelling cell surfaces with a wide range of applications, including cell motility, endocytosis and transmembrane signalling. MiCellAnnGELo employs the cross-platform (Mac/Unix/Windows) Unity game engine and is available under the MIT licence at https://github.com/CellDynamics/MiCellAnnGELo.git, together with sample data. MiCellAnnGELo can be run in desktop mode on a 2D screen or in 3D using a standard VR headset with a compatible GPU. Supplementary data are available at Bioinformatics online.
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