New Galaxy Tool: BiaPy – Deep Learning for Bioimage Analysis in Galaxy

We are excited to announce that the powerful bioimage analysis toolkit BiaPy is now available as a fully integrated tool within Galaxy. Researchers can now perform advanced deep-learning-based workflows for image segmentation, classification, and reconstruction. With BiaPy accessible through the Galaxy Tool Shed (version 3.6.5 + galaxy0), Galaxy users can harness BiaPy’s flexible network architectures and pretrained models from the BioImage Model Zoo and TorchVision in a familiar, data-analysis-centric interface.

We encourage all Galaxy users, especially those working in microscopy, histology, cell biology, high-content screening, and spatial-omics imaging, to explore BiaPy’s capabilities, whether segmenting complex tissue structures, classifying phenotypes at scale, or reconstructing volumetric image stacks. BiaPy in Galaxy offers a new level of accessibility and reproducibility.

To get started:

1. Visit the BiaPy tool in Galaxy.
2. Learn more about BiaPy in our documentation. Check out also the available workflows here.
3. Try a Galaxy workflow: upload an example image, run BiaPy segmentation, and link results to downstream Galaxy tools.
4. Share your workflows and feedback: join the Galaxy Image Analysis Community in Galaxy and the Euro-BioImaging FAIR Image Data Workflows Expert Group.

We look forward to seeing how the community uses BiaPy within Galaxy to push the boundaries of image-based science and reproducible research.