S.G. Djorgovski and S Lombeyda, Caltech

Medicine now collects vast and growing amounts of highly complex, and often multidimensional data from a variety of sources. Effective, intuitive data visualization is the bridge between the informational content of the data, and human experts' understanding and informed pattern recognition. Moreover, data fusion between different imaging modalities can revel important features that are not obvious in the data sets taken individually. Better data visualization that makes clearer sense of the data and pathologies in context of the larger framework, can thus lead to better clinical outcomes. Modern extended reality (XR) technologies can further provide valuable insights in the situations where the local 3-D context is important, or where a sheer complexity of imaged scene is difficult to navigate through with the standard 2-D displays.

We will describe our approach and experiments with advanced medical data visualization, and optimal, user-centric approaches that mix 2-D and 3-D visualization modalities.