Python-based software for generalized object instance segmentation from (cryo-)electron microscopy micrographs/tomograms. The software package is built on a general workflow where predicted semantic segmentation is used for instance segmentation of 2D/3D images.
- Robust and high-throughput semantic/instance segmentation of all microtubules:
-
- Supported file formats: [.tif, .mrc, .rec, .am]
- Supported modality: [ET, Cryo-ET]
- Supported Ã… resolution: [any best results in 1-40 Ã… range]
- 2D micrograph modality microtubule segmentation will come soon!
- Robust and high-throughput semantic/instance segmentation of membranes:
-
- Supported file formats: [.tif, .mrc, .rec, .am]
- Supported modality: [EM, ET, Cryo-EM, Cryo-ET]
- Supported Ã… resolution: [all]
- High-throughput semantic/instance segmentation of actin [Beta]
- Fully automatic segmentation solution!
- Napari plugin [Coming soon]
- Cloud computing [Coming soon]
DOI [Microscopy and Microanalysis]
Kiewisz R., Fabig G., Müller-Reichert T. Bepler T. 2023. Automated Segmentation of 3D Cytoskeletal Filaments from Electron Micrographs with TARDIS. Microscopy and Microanalysis 29(Supplement_1):970-972.
Link: NeurIPS 2022 MLSB Workshop
Kiewisz R., Bepler T. 2022. Membrane and microtubule rapid instance segmentation with dimensionless instance segmentation by learning graph representations of point clouds. Neurips 2022 - Machine Learning for Structural Biology Workshop.
- TARDIS-em v0.2.6 (2024-05-22):
-
- Added actin segmentation
- Improvement from Microtubule and Membrane prediction with updated models
- Added option for scripting TARDIS predictions
- Added visualization for semantic and instance predictions
- TARDIS build in results visualization
- Bug fixes
- Documentation tutorials
- Pypi and Conda releases
- Re-trained DIST model using simulated datasets
- Build 2 model for:
-
- filaments and general 2D structures
- 3D objects like membranes mitochondria LiDAR data etc.
For more examples and advanced usage please find more details in our Documentation
- Install TARDIS-em:
pip install tardis-em
or
conda install tardis-em -c rrobert92
- Verifies installation:
tardis
Full tutorial: 3D Actin Prediction
recommended usage: tardis_actin [-dir path/to/folder/with/input/tomogram]
advance usage: tardis_actin [-dir str] [-out str] [-ps int] [-ct float] [-dt float]
[-pv int] [-px float] ...
TBD
Full tutorial: 3D Microtubules Prediction
Data source: Dr. Gunar Fabig and Prof. Dr. Thomas Müller-Reichert, TU Dresden
recommended usage: tardis_mt [-dir path/to/folder/with/input/tomogram]
advance usage: tardis_mt [-dir str] [-out str] [-ps int] [-ct float] [-dt float]
[-pv int] [-px float] ...
Full tutorial: 2D Membrane Prediction
Data source: Dr. Victor Kostyuchenko and Prof. Dr. Shee-Mei Lok, DUKE-NUS Medical School Singapore
recommended usage: tardis_mem2d [-dir path/to/folder/with/input/tomogram] -out mrc_csv
advance usage: tardis_mem [-dir str] [-out str] [-ps int] ...
Full tutorial: 3D Membrane Prediction
Data source: EMPIRE-10236, DOI: 10.1038/s41586-019-1089-3
recommended usage: tardis_mem [-dir path/to/folder/with/input/tomogram] -out mrc_csv
advance usage: tardis_mem [-dir str] [-out str] [-ps int] ...