Bioimaging is an interdisciplinary science. In addition to biology itself, a deep understanding of optics, microscopy, fluorescence probes, image processing and image analysis is required. Due to this overwhelming need of diverse technologies and since it is rather unlikely a single individual can master all these topics, biologists and imaging scientists need to work together to achieve higher scientific goals. In order to facilitate this collaborative process, a strengthening of the bioimaging infrastructure is required. In the following, we focus on the image processing and analysis in bioimaging. We first briefly review the current status of the infrastructure and then explain the need for actions to promote a higher accessibility to bioimage analysis for biological researchers.

Among the overall bioimaging workflow, image processing and analysis come at the very last end. Microscope images are multidimensional data representing complex biological phenomena that involve biochemical reactions occurring within three dimensional spatial contexts. The major task of image processing and analysis is to computationally decrease the dimensionality of the problem under study, extract relevant quantitative information and conduct statistical data analysis.

Compared to the other technologies involved in bioimaging, image processing and analysis is unique in that its infrastructure is essentially made of computational tools. Hardware such as server and client machines, data storages and networks are the physical infrastructure for computation but not the main focus of this meeting. In turn software and its intrinsic capability for simple dissemination is the main target.

To organize and increase  in a scalable way the accessibility to image processing and analysis infrastructure within the European bioimaging community, its heavy dependence on human resource should be given a considerable attention.

Software is a pure product of human imagination. Its availability is solely dependent on the effort of computational scientists and programmers who create algorithms and implement them. We call these individuals “developers”. They create image processing algorithms, design their efficient implementations allowing faster computations, and design graphical user interfaces to simplify the user interactions. The outcome of their efforts ranges from general algorithms that could be used as basis for many types of applications to specific solutions limited to certain biological phenomena. The developers are hence algorithm developers and programmers, but in many cases algorithm developers also take the role of programmers.

As the number of image processing / analysis software and the diversity of image processing / analysis algorithms grew, professional knowledge to combine multiple image processing libraries and tools to construct complex workflows has increasingly become important. For this assembly task, insights in biology, image processing, various computational libraries, computer programming languages and statistics are necessary. Former developers were in many cases taking this role simultaneously, but recently a community of professionals specialized in assembling tools for such customized tasks is growing. They are mostly biologists, engineers and physicists and we will call this new type of professionals “analysts”.

Existing software packages already make available a rich range of tools for processing and analysis of microscope images. They are however constantly evolving and the number of functions is steadily growing. With so many choices offered to the users, the problem to choose the best tool to answer a specific question is not trivial, and sometimes extremely complex. Many high end packages are open source and readily accessible but bridging that accessibility to a specific demand is missing. The enhancement and strengthening of an human network capable of boosting this optimization and allowing a better usage of the existing software through collaborations / consultations / teachings is equally important.
To organize and increase the accessibility to image processing and analysis infrastructure within the European bioimaging community in a scalable way, its heavy dependence on human resource itself should be given with a considerable attention.

For this reason, we briefly overview the activities of developers and analysts. To assess the future of these activities, career paths will also be examined.