Imaging is one of the most powerful tools available to the modern biologist and recent advances in quantitative microscopy and image analysis have greatly accelerated our understanding of many complex and dynamic processes in basic biological and biomedical research. While commercial and closed-source software programs will always play a key role in image analysis, open-source programs are needed to advance new algorithm and method development and deployment to a diverse audience. The public domain image analysis program """"""""ImageJ,"""""""" maintained and developed by Wayne Rasband at the National Institutes of Health, is a widely used tool for image analysis in the biological sciences. Due to its ease of use, flexible scripting language and plug-in architecture, ImageJ has found itself being used effectively by the non-programmer, the amateur programmer, and the professional programmer alike. However, any successful software project, after a period of sustained growth and the addition of functionality outside the scope of the program's original intent, benefits from a subsequent period of scrutiny and refactoring, and ImageJ is no exception. Such review helps the program to remain accessible to newcomers, powerful enough for experts, and relevant to an evolving community. The pressing needs of the existing ImageJ community as well as of researchers who are hindered from joining the community due to limitations in ImageJ lead us to propose three aims of maximal benefit:
Aim I - Improve the ImageJ core architecture Improvements in core architecture are required for the development and stability of the ImageJ project, as well as its interoperability with other software and its ability to support new features and applications. This will involve (a) Separating the data model from the user interface, (b) Introducing an extensions framework for algorithms, and (c) Broadening the image data model.
Aim II - Expand functionality by interfacing ImageJ with existing open-source programs To ensure that development proceeds in a practical direction that maximizes interoperability, we will interface the improved ImageJ framework with two existing open-source biology applications, VisBio (multidimensional visualization) and CellProfiler (object identification and measurement). These will give ImageJ improved functionality and serve as examples for other software seeking to harness ImageJ similarly.
Aim III - Grow community-driven development while maintaining compatibility ImageJ has a strong, established user base, with thousands of plugins and macros designed to perform a wide variety of tasks. Consequently, reckless changes to the ImageJ platform may break existing code and drive away existing users. To foster participation, understanding, and enthusiasm from a growing community, we propose the adoption of several """"""""best practices"""""""" in line with other modern, successful open-source projects, which when taken together will build on ImageJ's solid foundation of community-driven development.
Imaging is one of the most powerful tools available to the modern biologist and recent advances in quantitative microscopy and image analysis have greatly accelerated our understanding of many complex and dynamic disease processes. While commercial and closed source programs will always play a key role in image analysis, the continued development of ImageJ as a public domain imaging processing tool is needed for new algorithm and method development and deployment to a diverse audience for biological and biomedical research.
|Rueden, Curtis T; Schindelin, Johannes; Hiner, Mark C et al. (2017) ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18:529|
|Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W (2017) ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability. Bioinformatics 33:629-630|
|Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C et al. (2015) The ImageJ ecosystem: An open platform for biomedical image analysis. Mol Reprod Dev 82:518-29|
|Pitrone, Peter G; Schindelin, Johannes; Stuyvenberg, Luke et al. (2013) OpenSPIM: an open-access light-sheet microscopy platform. Nat Methods 10:598-9|
|Buschke, D G; Vivekanandan, A; Squirrell, J M et al. (2013) Large particle multiphoton flow cytometry to purify intact embryoid bodies exhibiting enhanced potential for cardiomyocyte differentiation. Integr Biol (Camb) 5:993-1003|
|Schneider, Caroline A; Rasband, Wayne S; Eliceiri, Kevin W (2012) NIH Image to ImageJ: 25 years of image analysis. Nat Methods 9:671-5|
|Carpenter, Anne E; Kamentsky, Lee; Eliceiri, Kevin W (2012) A call for bioimaging software usability. Nat Methods 9:666-70|
|Schindelin, Johannes; Arganda-Carreras, Ignacio; Frise, Erwin et al. (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods 9:676-82|
|Eliceiri, Kevin W; Berthold, Michael R; Goldberg, Ilya G et al. (2012) Biological imaging software tools. Nat Methods 9:697-710|
|Kamentsky, Lee; Jones, Thouis R; Fraser, Adam et al. (2011) Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software. Bioinformatics 27:1179-80|