SVCell is a teachable image recognition and data analysis software for microscopy imaging.

Its patented recognition technologies can accurately and reliably detect, segment, track, measure, discover, classify, monitor and screen for cellular and subcellular phenotypes and events in microscopy images and movies.

SVCell has advanced, patented learning technologies and teaching interfaces that enable scientists and technicians to quickly and easily create accurate analysis with performance on par with custom written software, using a simple “teach by example” interface – guided by their biological knowledge rather than image processing expertise. Novel, high performance applications can be developed with low cost, minimum risk, and limited time and effort.

SVCell is platform independent and easy to integrate. It is both a development and execution platform that can be flexibly integrated as an execution component ranging from complete behind-the-scenes integration to being the front end graphical interface driving the solution.

SVCell incorporates next generation time-lapse image analysis and tracking technologies developed in part with funding from the National Institutes of Health (NIH) under multiple Small Business Innovative Research (SBIR) Programs.