The scanR high-content screening (HCS) station provides fully automated image acquisition and data analysis. Version 3.3 improves the deep-learning technology's capabilities to reliably separate objects in biological samples using instance segmentation, the ability to detect and delineate distinct objects of interest in an image. Accurate object segmentation: raw data (left), standard threshold (middle), TrueAI instance segmentation (right). Instance segmentation reliably separates difficult-to-distinguish objects that are very close together, such as cells or nuclei in colonies or tissue. The deep-learning technology can detect cells, nuclei and subcellular objects, and extract features from a list of over 100 object parameters.