Speaker
Description
Analyzing large amounts of microscopy images in a FAIR manner is an ongoing challenge, turbocharged by the large diversity of image file formats and processing approaches. Recent community work on an OME next-generation file format offers the chance to create more shareable bioimage analysis workflows. Building up on this and to address issues related to the scalability & accessibility of bioimage analysis pipelines, the BioVisionCenter is developing Fractal, an open-source framework for processing images in the OME-Zarr format. The Fractal framework consists of a server backend & web-frontend that handle modular image processing tasks. It facilitates the design and execution of reproducible workflows to convert images into OME-Zarrs and apply advanced processing operations to them at scale, without the need for expertise in programming or large image file handling. Fractal comes with pre-built tasks to perform instance segmentation with state-of-the-art machine learning tools, to apply registration, and to extract high-dimensional measurements from multiplexed, 3D image data at the TB scale. By relying on OME-Zarr-compatible viewers like napari, MoBIE and ViZarr, Fractal enables researchers to interactively visualize terabytes of image data stored on their institution’s remote server, as well as the results of their image processing workflows.
| Authors | Joel Lüthi*, Gustavo Quintas Glasner de Medeiros, Tommaso Comparin, Lucas Pelkmans, Prisca Liberali, Virginie Uhlmann |
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| Keywords | OME-Zarr, OME-NGFF, Fractal, Image Analysis, Workflows, Web, FAIR |
