pathml/pathml repository overview

⁠PathML

GitHub⁠ | Docs⁠ | Homepage⁠

A toolkit for computational pathology and machine learning.

• Build modular, fully-customizable preprocessing pipelines for gigapixel-scale images
• Unified API for H&E, IHC, fluorescence, and spatial omics images
• Support for 160+ file formats
• Fast dataloaders for integrating with the broader ML ecosystem (PyTorch, Tensorflow, Jax, etc.)
• Integration with broader single-cell analysis ecosystem (Scanpy, Squidpy, etc.) via AnnData standard

⁠View documentation⁠

Tutorials, example vignettes, technical notes, and a complete API reference can be found at docs.pathml.org⁠

⁠Installing

Please refer to installation instructions on the PathML GitHub repository⁠

⁠Citing

If you use PathML in your work, please cite our paper:

Rosenthal J, Carelli R, Omar M, Brundage D, Halbert E, Nyman J, Hari SN, Van Allen EM, Marchionni L, Umeton R, Loda M. Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology. Molecular Cancer Research, 2021. DOI: 10.1158/1541-7786.MCR-21-0665⁠

⁠License

The GNU GPL v2 version of PathML is made available via Open Source licensing. The user is free to use, modify, and distribute under the terms of the GNU General Public License version 2.

Commercial license options are also available.

⁠Contact

Questions? Comments? Suggestions? Get in touch!

[email protected]⁠