Organoids are microscopically small patient-derived 3D organs that can be cultivated in the laboratory over months mimicking human organs and their functions in vitro. These mini-organs have a human genetic background, maintain disease traits in vitro and are currently available for almost every human organ. Due to these advantages, organoid research and its commercial applications are rapidly evolving and increasingly used. Given the high variability of these complex 3D structures, classical cell culture-based image quantification tools techniques do not accurately capture organoids in microscope images. This has resulted in much image quantification at our laboratory - like in many others - being performed using manual time-consuming tools with a high researcher variability. In sum, there is a global challenge to in a standardized manner quantify organoid experiments. The overall objective of this project was to develop the first Software as a Service (SaaS) toolbox explicitly tailored to organoid imaging, building upon powerful AI-based algorithms for cutting-edge image quantification and independent of the underlying microscope and culture system hardware. The SaaS will provide a user-friendly approach to upload brightfield and immunofluorescence microscope images and videos of organoid cultures, which can then automatically be quantified by AI-models generating a range of organoid metrics. Overall, the provided automation envisioned would drastically reduces analysis time, promotes accurate phenotypical organoid analyses and ensures standardization of results between different researchers, culture conditions, and imaging hardware.
