![]() Imagej citation software#Additionally, as a project that welcomes source-code contributions, ImageJ attracts end users and software programmers alike. Imagej citation code#A few characteristics set this program apart from the competitors, though, and these nuances are maintained today: application and source code were available free of cost, it had a very simple user interface, and could run on affordable desktop machines. NIH Image entered a field already crowded with highly advanced scientific image-processing software that was targeted at computer scientists (e.g., Cristy et al., 1994 Konstantinides and Rasure, 1994). In 1987, Wayne Rasband, who at that time was working at the National Institute of Health (Bethesda, MD), released “NIH Image”, the predecessor to ImageJ. Rather than paraphrasing these excellent resources, this review will focus on the ImageJ project (Schneider et al., 2012) as a case study of how open-source software fosters an ecosystem of software tools, making an abundance of image-analysis methods and approaches easily accessible to the scientific community. There are also entire books focusing on the topic of image processing written for specific scientific disciplines in microscopy alone, readers can find excellent resources for video image processing (Inoue, 1981), digital microscopy (Sluder and Wolf, 2007), and digital imaging in optical microscopy ( ). Thus, life scientists needed accessible methods to execute image processing and analysis techniques to quantitatively support their research.Ī large number of reviews have been written on the subject of biomedical image processing and analysis tools in general (e.g., Eliceiri et al., 2012) and on tools to perform specific tasks (e.g., Pham et al., 2000 Meijering et al., 2006). Advances in biomedical image-processing techniques have allowed for the corroboration of research outcomes by quantifying them in a rigid, statistical manner while simultaneously raising the bar for life science research when it comes to substantiating scientific observations. Compared to conveniently uniform footage (e.g., from a video camera), biomedical images require substantial knowledge about the physical intricacies of the optics involved, coupled with textbook computer vision expertise, for sound image processing. As the field of image processing matured (e.g., Castleman, 1996), computer-vision experts developed specialized techniques that could be applied to biomedical images.īiomedical image processing is a subset of computer-vision research with its own specific challenges-namely, low-light conditions required to keep the imaged specimen alive. The aim is to use computational processes to accelerate repetitive tasks while also obtaining quantitative results, since statistical results are much more compelling, scientifically speaking, than qualitative observations. © 2015 Wiley Periodicals, Inc.Įver since digital imaging equipment entered the world of science, life scientists have collaborated with computer scientists to apply image-processing techniques to analyze biomedical data. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. ![]()
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