In medicine, a steadily growing data complexity often paralleling new developments in image and non-image data acquisition is observed. This complexity poses many challenges on data processing, visualization, and exploration. It renders the design of overview visualizations, which convey all interesting patterns contained in the data, impossible. Instead, automatic data analysis techniques must be tweaked based on expert knowledge and combined with interactive visualizations for the retrieval of such patterns. This approach is at the heart of the field visual analytics.

In this talk, I present visual analytics approaches to investigating complex data from clinical medicine and epidemiology. In particular, the talk's main topics are (1) the integration of data mining and interactive visualizations for the visual analysis of simulated cerebrovascular hemodynamic data, (2) a methodology for joint visual analytics of image and non-image epidemiological population study data, and (3) the visual verification of cancer staging for therapy decision support.


Steffen Oeltze-Jafra Dr. habil. Steffen Oeltze-Jafra is Scientific Director of Digital Patient and Process Model and Group Leader at the Innovation Center Computer Assisted Surgery (ICCAS), University of Leipzig, Germany. His research interests are in visual analytics of clinical, biological and epidemiological data, digital patient modeling, and clinical decision support. In 2016, Steffen received a habilitation (venia legendi) in computer science from the University of Magdeburg (UoM). In 2010, he received his Ph.D. in computer science and in 2004, his diploma (M.Sc.) degree in computational visualistics from the the same university. In 2017, Steffen won the Dirk Bartz Prize for Visual Computing in Medicine from Eurographics (2nd place). In 2004 and 2008, he received the "Karl-Heinz-Höhne" Award (2nd and 1st place).