Fiji Is Just ImageJ – an open source platform for collaborative research in biological image analysis

Most primary data in biology are in the form of images. The recent quantum leaps in microscopy have brought about an almost exponential increase in the amount and complexity of imagery that biologists collect. It is no longer possible to extract meaning from these image datasets by simply looking at them, which necessitated the formation of a new branch of scientific inquiry called Bioimage Informatics that combines biology and computer science and focuses on extracting meaningful information from massive amounts of images of biological systems. The July issue of Nature Methods maps the recent developments in this nascent but already thriving field with commentaries, reviews and research papers covering various aspects of the discipline (Figure 1a). The issue introduces, among others, Fiji (Fiji Is Just ImageJ) an open source platform for doing research in biological image analysis (Figure 1b Schindelin et al. 2012).

HFSP Young Investigator Grant holder Pavel Tomancak and colleagues
authored on Mon, 16 July 2012

Fiji has been to a large extent developed by the programmers in the Tomancak lab (Program Grant 2008 and 2012) at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) where the very active wiki site for the project is hosted (

Figure: (a) Cover of Nature Methods July 2012 issue containing Focus on bioimage informatics. The cover has been reconstructed from images of gene expression patterns in Drosophila embryogenesis using an open source Fiji plugin called Cover Maker ( (b) The logo of Fiji (Fiji Is Just ImageJ is a self-referential acronym indicating the roots of Fiji in ImageJ). The relationship between Fiji and ImageJ is similar to how Ubuntu relates to Linux - Fiji is a distribution of ImageJ. (c) Google Maps showing the geolocations of computers that updated Fiji over the period of one week. The interactive version of the map can be seen at

Fiji is a distribution of a very popular open source package ImageJ that has been serving the image analysis needs of biologists over the past decades (Schneider et al. 2012). Fiji enhances ImageJ by updating the infrastructure of the program, using modern software engineering practices. For the users nothing changes as the program looks and feels like classical ImageJ, however it comes with a curated selection of so-called plugins (software components extending ImageJ that can be installed separately) that address most of the typical image analysis tasks biologists encounter in their research. Many of the plugins are inherited from ImageJ while others are developed specifically for Fiji. These are usually more complex solutions using the advanced programming facilities of Fiji, such as stitching of large 3d images from overlapping tiles, reconstruction and analysis of multi-view Selective Plane Illumination Microscopy (SPIM) data or assembly of 3d volumes from massive serial section electron microscopy image sets (consisting of tens of thousands of images; Saalfeld et al. 2012).

Fiji provides an innovative distribution system, which allows the users to update their installation every time they start the program, pulling new image analysis solutions from main server in Dresden or from alternative, private update sites offered by plugin developers around the world. In this way, users can build and maintain their custom Fiji installation, staying up-to-date and in direct contact with the plugin authors. Fiji also offers a broad selection of scripting languages, many of which are familiar to biologists, that can be used to build custom image analysis solutions with minimal knowledge of computer programming. Similarly to plugins, scripts can also be shared through the updater system creating a powerful and diverse ecosystem.

Fiji aims to facilitate productive collaboration between biologists and computer scientists in order to solve complex image analysis problems associated with massive multi-dimensional imagery produced by modern microscopy technologies. In order to attract top-notch software developers and transfer innovative algorithms from the fields such as computer vision and signal processing, the Fiji team developed several powerful libraries (such as ImgLib) that simplify the process of transforming abstract ideas into usable programs capable of running on large bioimage datasets. These ‘under the hood’ improvements will hopefully make the platform more attractive to computer science professionals willing to take on the challenges posed by the biological image datasets.

The Fiji platform has over the past few years attracted a huge following and is used as an open source image analysis solution in most academic institutions around the world (current usage statistics indicate 25,000 users and 125,000 unique hits per month to the Fiji wiki; Figure 1c). The platform is open to collaborations with other similarly minded projects in the bioimage informatics field many of which are also highlighted in the Nature Methods focus (for review see Eliceiri et al. 2012). Fiji developers meet regularly for two weeks coding sprees called ‘hackathons’ and these events are increasingly attended by representatives of the other open source projects building bridges among them. Over time this collaborative culture will lead to better integration between the projects, each of which has its strengths and weaknesses, and benefit the biology community. Nevertheless, it will not happen without support from funding agencies and Institutions since even open source software development is not free and requires sustainable long-term support in the academic environment (see commentary by Cardona and Tomancak 2012)

Bioimage Informatics is a young field, but it is also dynamically growing and full of opportunities. Gene Myers one of the pioneers of bioinformatics sees a lot of parallels between the early days of sequence analysis and the current status of the bioimage analysis field (Myers 2012). Maybe it is time for some of bioinformatitions to jump the ship and apply their talents in the bioimage informatics area.


Fiji - an open source platform for biological image.  Schindelin J., Arganda-Carreras I., Frise E., Kaynig V., Longair M., Preibisch S., Rueden C., Saalfeld S., Schmid B., Tinevez J., Hartenstein V., Eliceiri K., Tomancak P., Cardona A. (2012) Nature Methods 9(7), 676-682 PMID: 2274772

Additional References

NIH Image to ImageJ: 25 years of image analysis.  Schneider C.A., Rasband W.S., Eliceiri K.W. (2012). Nature Methods 9, 671–675 PMID: none (Historical perspective).

Elastic Volume Reconstruction from Series of Ultra-thin Microscopy Sections. Saalfeld S., Fetter R., Cardona A., Tomancak P. (2012) Nature Methods 9(7), 717-720 PMID: 22688414.

Biological Imaging Software Tools. Eliceiri K. W., Berthold M. R., Goldberg I. G., Ibanez L., Manjunath B. S., Martone M. E., Murphy R. F., Peng H., Plant A. L., Roysam B., Stuurmann N., Swedlow J.R., Tomancak P., Carpenter A. E. (2012) Nature Methods 9(7), 697-710 PMID: 22743775.

Current challenges in open-source bioimage informatics. Cardona A., Tomancak P. (2012). Nature Methods 9(7), 661-665 PMID: 22743770.

Why bioimage informatics matters. Myers G. (2012) Nature Methods 9, 659–660 PMID: 22743769.

Pubmed link