There are numerous areas in the life sciences where people need to be able to classify images that are generated as part of large-scale efforts from cell assay screening, drug manufacturing all the way to post-market screening for counterfeit packaging and tablets. Traditionally these activities have been performed by teams of people laboriously looking through image sets. The challenge with this traditional approach is that things can be missed because there simply isn’t enough resource to scan all images effectively. Deep learning approaches fundamentally shift this paradigm. AI approaches can be trained to look for patterns and objects in images in a much more “human-like” way without rule-sets and therefore can be utilized as powerful tools in scanning and analyzing large image corpora or real-time streaming image sources. But different from humans, AI agents can scan through all images in a comprehensive manner thereby much more effectively analyzing the full image data set.

Vyasa Cortex enables users to apply a wide range of deep learning image analytics to life sciences related image sets. Vyasa has finely-tuned these algorithms for specialized life sciences images types. Furthermore, the highly scalable Cortex platform makes it easy to connect to large image repositories or image streams and apply image analytics to those sources with just a few clicks of a mouse.