Image processing is a solid field where many algorithms have been developed to improve image quality, to extract features, to compress the information, to segment objects, to classify patterns, to track objects, to estimate model parameters in presence of noise and to interactively visualize the data. These advances have been made possible by the interactions between researchers in the field of signal processing, computer vision, mathematics, statistics, machine learning and computer science. Some of these researchers (developers) became specialized in treating microscope images in collaboration with biologists and contributed many software packages and tools (many are also lead by biologists).
These contributions can be seen in a glance in the webpage of the Open Bio Image Alliance (OBIA), as well as the developer on-going gatherings.
Information exchange and human networks have been established through these meetings. The career path of developers inherits that of computer scientists and programmers. Computer scientists have their academic position in computer science, electrical engineering and signal processing departments or image processing position in biological / medical institutes. They publish their outcome of developments in computer science and signal processing journals as well as in biological journals as collaborators, which will be the credit for their scientific career.
Analysts bridges the gap between developers and biologists. The gap exists since the demands of biologists could ultimately be summarized to “single click and does all”. Such automation is possible for some trivial tasks but in many cases the complexity of modern Bioimage Analysis methods hinders the full automation. Every Bioimaging project is unique hence the image analysis, the final step of bioimaging, is also unique and cannot escape from some assembling and customizations. Here analysts come into play to create optimal protocols of image analysis.
In addition to customization of image analysis protocols, another major activity of most of analysts is teaching. Teaching of basics on image processing and analysis techniques shifts up the level of “Image Processing and Analysis literacy” in their belonging institute, which collectively has positive effect in promoting high-level image analysis in that local Bioimaging community.
The analyst is a new type of profession and their number is limited. The first precursory gathering of analysts took a form of course to teach image analysis to biologists in 2013 (EMBL Master Course on BioImage Data Analysis 2013, BIAS 2013). The prominent outcome of analysts working together was course textbooks written through collaborative editing and peer reviewing. Through this process, we learned creative ideas from others on how each has been solving various Bioimage Analysis problems. As each of us had been more-or-less working individually and locally, exchange of knowledge were highly valuable and enlightening.
The background of analysts is diverse: Physicists, Computer Scientists, Electrical Engineers, Physical Chemists and Biologists. There is no established career path for becoming analysts, but a need of diverse knowledge as stated already. Compared to developers who have conventional criteria for evaluating their careers, analysts are currently evaluated only by words of mouth. An increased visibility of the their work is required both for stabilizing this new career path and at the same time for the employers to evaluate candidates.
Scientists, engineers or students who, in collaboration with analysts or developers, or independently, perform BioImage processing & analysis to ultimately answer scientific questions or support scientific and technological development.
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