The research department „Stochastic Relational AI in Healthcare“ (StarAI) deals with intelligent systems in healthcare, that calculate optimal actions under uncertainty by observing their environment and creating models based on data.
Intelligent systems in healthcare build models by observing their environment and evaluating data in order to calculate actions optimally. In doing so, they must also deal with uncertainty. One exciting application under uncertainty is image registration, where areas on specific images are linked to areas on other images. One use case is matching organs in MRI images to the same organs on CT images. One approach to enhance registration is to use a cycle-GAN model to synthesize images before registration. In that approach, images from one domain are transformed into images from the other domain.
The team from the Stochastic Relational AI research area will demonstrate this synthesis using the example of synthesizing horses to zebras and vice versa. Visitors can place a Schleich© horse play figure, or a Schleich© zebra live in front of a camera. The live stream on the monitor shows the image synthesis resulting in a live transformation of the two animals.