JIPipe: Designing automated image analysis pipelines without programming

CONTACT [email protected] Research Group Systems Biology / Bioinformatics References: [1] Surname, N., Surname, N. N., and Surname, N. N. (2008). Nature Reviews Immunology Picture of you CONTACT [email protected] Research Group Applied Systems Biology References: [1] Rueden, C. T., Schindelin, J., Hiner, M. C., DeZonia, B. E., Walter, A. E., Arena, E. T., & Eliceiri, K. W. (2017). ImageJ2: ImageJ for the next generation of scientific image data. BMC bioinformatics, 18(1), 1-26. [2] Haase, R., Royer, L. A., Steinbach, P., Schmidt, D., Dibrov, A., Schmidt, U., ... & Myers, E. W. (2020). CLIJ: GPU-accelerated image processing for everyone. Nature methods, 17(1), 5-6. [3] Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. Nature Methods, 18(1), 100-106. JIPipe: Designing automated image analysis pipelines without programming Ruman Gerst1,2, Zoltán Cseresnyés1, and Marc Thilo Figge1,3 1 Applied Systems Biology, Leibniz Institute for Natural Product Research and Infection Biology – Hans-Knöll-Institute, Jena, Germany 2 Faculty of Biological Sciences, Friedrich-Schiller-University Jena, Germany 3 Institute of Microbiology, Faculty of Biological Sciences, Friedrich-Schiller-University Jena, Germany Java Image Processing Pipeline (JIPipe) is a plugin for ImageJ [1] that allows to create image processing pipelines without a script language. Instead users only have to design a flow-chart by connecting processing steps (nodes) to each other in a visual programming language. 🗹 500+ commonly used functions from ImageJ and popular plugins 🗹 Intuitive and modern user interface 🗹 Powerful annotation system for tracking metadata 🗹 Standardized & automated output to hard drive JIPipe integrates many image analysis functions, like image import, thresholding, contrast enhancement, edge detection, or extracting measurements from ImageJ and allows them to be run in a batch environment. Additionally, we included popular plugins like ... To allow even greater flexibility, you can utilize ImageJ Macro, Python, and R script nodes to write or re-use custom code inside the JIPipe environment. Image analysis powered by ImageJ GPU processing and Deep Learning More features via plugins JIPipe allows easy utilization of modern graphics hardware by including all functions provided by the powerful CLIJ2 [2] library for GPU processing. JIPipe's advanced data management automatically takes care of all technical details like converting images. Deep Learning has become a commonly used tool in image analysis. To allow anyone to make use of this technology, JIPipe includes Deep Learning libraries like Cellpose [3] - with full support for all functions and parameters, including training. A more generalized library for Deep Learning using Keras and Tensorflow is currently being developed, as well. JIPipe already provides many features, like the table processing algorithms, plotting, sorting and distributing data, user interaction during the pipeline, and more. Additional features can be easily developed in Java as ImageJ plugin, or created within a GUI tool that allows anyone to create new nodes. These are also automatically available from inside ImageJ, as JIPipe exports all its functions to ImageJ. JIPipe comes with its own graphical user interface that allows easy access to all functions. ① The graph editor to build the flow chart ② All settings are shown on the right-hand side ① ② JIPipe already integrates many popular software tools like ImageJ and Python into one easy-touse environment. JIPipe comes pre-packaged with support for GPU and Deep Learning tools like CLIJ and Cellpose. 🗹 Bio-Formats 🗹 OMERO 🗹 MorphoLibJ 🗹 FeatureJ 🗹 Multi-Template-Matching Plugins GUI Editor Java API JIPipe can be easily extended with plugins. 🗹 Nodes 🗹 Data types 🗹 Menus 🗹 ...