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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.
Henning Paul-Julius Stahlberg, Marta Di Fabrizio, Amanda Jennifer Lewis, Christel Genoud, Notash Shafiei, Domenic Burger, Daniel Andrea Constantin Stähli, Cornelius Laurentius Matheus van den Heuvel
Suliana Manley, Jenny Sülzle, Laila Abdelaziz Abdelmoniem Elfeky