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

Author:

Platt Adam1,Lutton E Josiah1ORCID,Offord Edward1,Bretschneider Till1ORCID

Affiliation:

1. Department of Computer Science, University of Warwick , Coventry CV4 7AL, UK

Abstract

Abstract Summary 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. Availability and implementation 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 information Supplementary data are available at Bioinformatics online.

Funder

Biotechnology and Biological Sciences Research Council

Engineering and Physical Sciences Research Council

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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