Visual analytics of single cell microscopy data using a collaborative immersive environment

Abstract

Understanding complex physiological processes demands the integration of diverse insights derived from visual and quantitative analysis of bio-image data, such as microscopy images. This process is currently constrained by disconnects between methods for interpreting data, as well as by language barriers that hamper the necessary cross-disciplinary collaborations. Using immersive analytics, we leveraged bespoke immersive visualizations to integrate bio-images and derived quantitative data, enabling deeper comprehension and seamless interaction with multi-dimensional cellular information. We designed and developed a visualization platform that combines time-lapse confocal microscopy recordings of cancer cell motility with image-derived quantitative data spanning 52 parameters. The integrated data representations enable rapid, intuitive interpretation, bridging the divide between bio-images and quantitative information. Moreover, the immersive visualization environment promotes collaborative data interrogation, supporting vital cross-disciplinary collaborations capable of deriving transformative insights from rapidly emerging bio-image big data.