Cognex Deep Learning locates rack samples
Graphical programming environment for deep learning-based industrial image analysis
Clinical diagnostic equipment manufacturers rely on machine vision for automated deck population assessment. Liquid handling systems, such as analyzers or IVD equipment, must detect the location and orientation of racks and their vessels in order to pipette and process samples properly. Incomplete racks can impair workflows and cause costly machine assists. These highly automated systems sometimes encounter failures resulting from misaligned or absent test tubes or caps that haven’t been removed. Vessels and tubes vary in size, dimensions, and cap type by manufacturer, making it difficult for the machine handling system to predict the position of parts on their decks.
Cognex Deep Learning excels at locating similar objects in bulk. With the location tool, any lab technician is able to fixture tray images, teaching the software to identify and count individual tubes based on their size, shape, and features. The location tool detects the location and orientation of microtiterplates and other racks on the IVD’s deck, as well as their sample tubes, despite their unpredictable and varying dimensions. Once Cognex ViDi has located the samples on the rack, traditional machine vision tools are used to align the samples and reagents for further processing.