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 Å resolution: [any best results in 1-40 Å 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 Å 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.

Full History

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

1. Install TARDIS-em:

pip install tardis-em

or

conda install tardis-em -c rrobert92

2. 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] ...