Today, the Chan Zuckerberg Initiative (CZI) announced funding for open-source software efforts to improve image analysis and visualization in biomedicine. Microscopy -- critical to modern cell biology -- generates large volumes of complex data that pose significant challenges for analysis and visualization. The funding will support developers ("Imaging Software Fellows") from three projects to develop and maintain software tools, and begin collaborating to help create a cohesive, shared ecosystem of resources that can accelerate basic research and benefit the entire field.
"Better imaging software will make it faster and easier for biologists to extract quantitative information from imaging data, and share their methods and results with others," said CZI Head of Science, Cori Bargmann. "These grants highlight the impressive but underappreciated work of academic software developers in this area. We're excited to work with our grantees to accelerate a fundamental field in biomedicine."
The CZI Imaging Software Fellows work on three critical and widely-used tools: scikit-image, FIJI / ImageJ, and CellProfiler. After several workshops, hackathons, and discussions with the imaging community, these three projects were identified as playing a critical role in the imaging ecosystem, and their developers demonstrated an interest in improving the interoperability and capabilities of their tools.
The grants will be administered by the Chan Zuckerberg Initiative DAF, a donor-advised fund of Silicon Valley Community Foundation. The Imaging Software Fellows will collaborate within their projects and with others through frequent communication, open software development, and regular hackathons and meetings, with all code released under maximally permissive open-source licenses.
CZI believes that leveraging technology, encouraging collaborations, and supporting shared resources can move science forward faster. To this end, computational biologists and software engineers from CZI will collaborate with the Imaging Software Fellows to better understand the current ecosystem and work together to identify new ideas.
More information on the three projects and Fellows is as follows:
scikit-image is a community-driven Python project consisting of a collection of algorithms for image processing available free of charge and free of restriction. With over 285 contributing developers, and 14,000 packages that depend on it, scikit-image plays a critical role across many domains of science, ranging from biomedical image processing to astronomy, and may things in between.
Juan Nunez-Iglesias, a Bioimage Analysis Research Fellow at Monash University in Australia, will work to advance both the technical capabilities and community growth and mentorship around base software libraries for image analysis in Python. Juan will focus on developing scikit-image while also collaborating to improve the surrounding ecosystem, including NumPy and SciPy (the basis of scientific computing in Python), CellProfiler (a graphical user interface for cell-based measurements in images), and dask (a library for computing on very large datasets).
ImageJ and Fiji:
ImageJ, an open-source Java program, was originally released in 1997 as a freeware image analysis program, and is one of the most-used tools for imaging scientists across the globe. ImageJ has a large audience of users and developers of varying skill levels, interests, and applications, and has since grown into the Fiji and ImageJ2 open-source platforms with over 1,000 plugins (and counting), which add key image analysis tools. ImageJ and related projects are cited in over 10,000 publications across a wide range of domains of biology.
Curtis T. Rueden, a Software Architect in the Eliceiri research group at the University of Wisconsin-Madison, will continue to develop ImageJ and Fiji and expand its contributions from non-programmers, amateur programmers, and professional developers alike. A concerted software engineering effort is needed to support emerging imaging paradigms and ensure Fiji's ability to handle the requirements of modern science. Curtis will assist in this engineering effort and lead efforts for collaboration between tools and projects in the open-source imaging community.
The open-source CellProfiler has been used in a wide range of experiments, analyzing images of specimens such as cells, yeast colonies, and worms in support of research on diseases ranging from breast cancer and leukemia, to liver disease and HIV. The software has been cited over 6,200 times since being published in October 2006.
Allen Goodman, a Senior Software Engineer at the Broad Institute of MIT and Harvard, working in the lab of Anne Carpenter, will support the existing open-source CellProfiler codebase as part of contributing to collaborative, open-source projects that will benefit the entire bioimaging software ecosystem. Goodman will focus on the most important collaborative projects needed to transition the bioimaging software ecosystem towards the use of deep learning and web-based applications. This will include a web application for evaluating segmentation algorithms that help analyze images, training a deep learning model to robustly detect nuclei across experimental setups, and creating a deep learning-based tool to classify cell types. Goodman will also assess and improve integration between CellProfiler and other key bioimaging software libraries, such as scikit-image.
The open-source software produced from this work aims to immediately improve microscopy image analysis and visualization for a wide community of researchers. And there's more: to help bring more engineering expertise to imaging, CZI also recently announced an open Request for Applications for the Imaging Scientists program, and we are actively exploring future mechanisms to continue to support this community.
About the Chan Zuckerberg Initiative:
The Chan Zuckerberg Initiative was launched in December 2015 by Mark Zuckerberg, founder and CEO of Facebook, and Priscilla Chan, a pediatrician and founder and CEO of The Primary School in East Palo Alto. The Chan Zuckerberg Initiative is a new kind of philanthropy that seeks to engineer change at scale. By pairing world-class engineering with grant-making, impact investing, policy, and advocacy work, CZI hopes to build a future for everyone. Initial areas of focus include supporting science through basic biomedical research and education through personalized learning. CZI is also exploring ways to address barriers to justice and opportunity - from criminal justice reform, to expanded access, to economic opportunity and affordable housing.