Unknown

Dataset Information

0

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


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.

SUBMITTER: Platt A 

PROVIDER: S-EPMC9869652 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

altmetric image

Publications

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

Platt Adam A   Lutton E Josiah EJ   Offord Edward E   Bretschneider Till T  

Bioinformatics (Oxford, England) 20230101 1


<h4>Summary</h4>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 labellin  ...[more]

Similar Datasets

| S-EPMC7612967 | biostudies-literature
2025-04-22 | GSE252228 | GEO
| S-EPMC1343588 | biostudies-literature
2022-06-14 | GSE178069 | GEO
| S-EPMC9708043 | biostudies-literature
| S-EPMC11308045 | biostudies-literature
| S-EPMC6208343 | biostudies-literature
| S-EPMC9397159 | biostudies-literature
| S-EPMC8428725 | biostudies-literature
| S-EPMC9399742 | biostudies-literature