The Center for Open Bioimage Analysis is a joint project between the labs of Dr. Kevin Elicieiri at University of Wisconsin and the Morgridge Institute, and Dr. Beth Cimini of the Broad Institute.
Quantifying images is now a critical, widespread need in biological research as light microscopy experiments continue to grow in scale, size, dimensionality, scope, modality, and complexity. Many biologists are missing out on the quantitative bioimaging revolution due to lack of effective algorithms and/or usable software for their needs. In particular, a major gap exists between point-and-click software for biologists and cutting-edge tools such as the deep learning revolution that has recently transformed computer vision. Biologists’ workflows are also becoming more complex; they must combine many image and data analysis tools to quantitatively interrogate biological systems.
The mission of the Center for Open Bioimage Analysis is to provide user-friendly tools that biologists of all skill levels can use to leverage the latest technology to get the most out of their images. It will catalyze the international community of developers working on the next generation of image analysis strategies, and ultimately pay for itself by making thousands of biologists’, computer scientists’ and software engineers’ work more efficient and impactful, accelerating research worldwide.
Community Engagement: We aim to serve as a nucleating force, organizing and creating readily available online bioimaging training materials, workshops, hackathons, and conferences, in order to serve biologists, microscopy facility staff, and algorithm/software developer communities.
Specific Aims:
1. Maintain state-of-the-art access to evolving image analysis methods in established user-friendly tools such as ImageJ, Fiji, CellProfiler, and Piximi
2. Improve access to and accessibility within open-source image analysis tools, embracing additional deployment approaches
3. Improve interoperability of open-source image analysis tools and methods, including cross-language interoperability across Java, Python, and JavaScript