Preprint:

JIPipe: Visual batch processing for ImageJ.

Gerst R*, Cseresnyés Z*, Figge MT (2022) JIPipe: Visual batch processing for ImageJ. ResSquare [Preprint]

*equal contribution

Abstract

The continuous development of new microscopy techniques requires the parallel evolution of image analysis workflows. ImageJ provides a high level of accessibility to bioimage processing, which is still impeded by the necessity of developing scripts to achieve reproducibility, and to comply to the FAIR principles. We provide a visual language termed JIPipe that allows the construction of an ImageJ workflow purely by designing a flowchart. We already included over 1000 functions from ImageJ and its plugins. In return, ImageJ is extended with custom-designed algorithms, thus forming a symbiotic relationship with JIPipe. Our software includes a fully reproduceable and standardized project format, zero-cost scalability of pipelines, as well as automated data saving into an open format. JIPipe was already utilized to solve numerous demanding image analysis tasks, showcasing its wide applicability and adaptability. JIPipe contributes towards making bioimage analysis more accessible, thereby fostering collaborations between experimentalists and computer scientists.

Leibniz-HKI-Authors

Zoltán Cseresnyés
Marc Thilo Figge
Ruman Gerst

Identifier

doi: 10.21203/rs.3.rs-1641739/v1