Our AI-based platform is built on cutting-edge technology and a progressive methodology
We have developed proprietary clinical-grade deep learning architectures that are tailored to pathology and achieve results on par with experts. Combining human experts with our AI leads to accuracies beyond current standards
Our team has already built secure, fast and robust AI systems for millions of users. We know what it takes to scale AI from the benign R&D setting to the noisy real world and systems with high regulatory demands in clinical diagnostics
Image analysis tools need to earn the trust of the experts. Modern methods in explainable AI (xAI) help to open the black box and are an essential component to achieve this trust. We use such methods to provide the needed guidance to pathologists and clinicians
In addition to labeled data, there is a wealth of images without annotations in pathology. We harvest this treasure and extract relevant patterns even from unannotated data by using specialised methods such as self-supervised learning and generative adversarial networks
We are a lead author of the German "Guideline for the development of deep learning based image analysis systems in medicine" by the German Institute for Standardization (DIN) "DIN SPEC 13266 & 13288: Leitfaden für die Entwicklung von Deep-Learning-Bilderkennungssystemen in der Medizin"). We have advised several members of the German parliament.
Image analysis in pathology is one of the most challenging visual tasks performed by humans. Finding tumor cells in large tissue slides is often like searching for a needle in a haystack. This challenge gets even harder when building systems that scale to the real world: what a tissue sample looks like can be different from lab to lab due to differences in preprocessing and stainings.
We solve these challenges by building systems based on artificial intelligence (AI) that work out of the box. Our BreastIHC is the first ever commercially available product that is able to detect tumor cells in arbitrary images of IHC-stained breast cancer tissue without the need for manual fine-tuning.