Imaging techniques (photography, microscopy, tomography, etc.) have long since become indispensable in the life sciences. A manual evaluation of the images is still difficult to reproduce, due to the large number of high-resolution images, it is practically impossible to do so in time and is rarely statistically significant. Software for the (semi-)automatic evaluation of images must, however, usually be developed specifically for the application. The Knowledge Engineering (FS KE) department of the IAS would therefore like to increasingly establish and expand digital image evaluation as a core competence with the aim of making this competence available for the benefit of all institutes in the department. In the context of digitisation, image analysis/evaluation is also a key competence which is currently still too little available but which is needed for the implementation of the strategic goals.

The Food Technology Research Group (FG LMT) at ILGI hopes to use fluorescence microscopy in addition to light microscopy for the structural elucidation of food. The evaluation of microscopy images is only possible optically with regard to qualitative (starch, protein, ...) and quantitative aspects (localisation). This type of evaluation depends on the person performing the analysis and is therefore difficult to reproduce. The newly acquired microscope of FG LMT is completely digital, which allows the use of an evaluation software. Especially with regard to a standardized, (semi-)automatic evaluation (and thus reproducible studies), the process of image evaluation should be digitalized and at the same time individualizable. For the FG LMT, this means a clear advantage compared to other research institutions in the field of process-accompanying analytics and thus clear support in achieving the strategic goals.

FG LMT's new microscope and its need for a specific evaluation software offer an ideal use case for the planned competence expansion of the IAS. Both institutes will benefit permanently from a long-term cooperation for the digitization of processes.