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Many scientific software platforms provide plugin mechanisms that simplify the integration, deployment, and execution of externally developed functionality. One of the most widely used platforms in the imaging space is Fiji, a popular open-source application for scientific image analysis. Fiji incorporates and builds on the ImageJ and ImageJ2 platforms, which provide a powerful plugin architecture used by thousands of plugins to solve a wide variety of problems. This capability is a major part of Fiji's success, and it has become a widely used biological image analysis tool and a target for new functionality. However, a plugin-based software architecture cannot unify disparate platforms operating on incompatible data structures; interoperability necessitates the creation of adaptation or "bridge" layers to translate data and invoke functionality. As a result, while platforms like Fiji enable a high degree of interconnectivity and extensibility, they were not fundamentally designed to integrate across the many data types, programming languages, and architectural differences of various software platforms.To help address this challenge, we present SciJava Ops, a foundational software library for expressing algorithms as plugins in a unified and extensible way. Continuing the evolution of Fiji's SciJava plugin mechanism, SciJava Ops enables users to harness algorithms from various software platforms within a central execution environment. In addition, SciJava Ops automatically adapts data into the most appropriate structure for each algorithm, allowing users to freely and transparently combine algorithms from otherwise incompatible tools. While SciJava Ops is initially distributed as a Fiji update site, the framework does not require Fiji, ImageJ, or ImageJ2, and would be suitable for integration with additional image analysis platforms., Comment: 33 pages, 11 figures

CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main CellProfiler program, CellProfiler has a plugins system that allows for the creation of new modules which integrate with other Python tools or tools that are packaged in software containers. The CellProfiler-plugins repository contains a number of these CellProfiler modules, especially modules that are experimental and/or dependency-heavy. Here, we present an upgraded CellProfiler-plugins repository, an example of accessing containerized tools, improved documentation, and added citation/reference tools to facilitate the use and contribution of the community., Comment: 17 pages, 2 figures, 1 table

ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs.