Visualization-guided evaluation of simulated minimally invasive cancer treatment

We present a visualization application supporting interventional radiologists during analysis of simulated minimally invasive cancer treatment. The current clinical practice employs only rudimentary, manual measurement tools. Our system provides visual support throughout three evaluation stages, starting with determining prospective treatment success of the simulation parameterization. In case of insufficiencies, Stage 2 includes a simulation scalar field for determining a new configuration of the simulation. For complex cases, where Stage 2 does not lead to a decisive strategy, Stage 3 reinforces analysis of interdependencies of scalar fields via bivariate visualization. Our system is designed to be immediate applicable in medical practice. We analyze the design space of potentially useful visualization techniques and appraise their effectiveness in the context of our design goals. Furthermore, we present a user study, which reveals the disadvantages of manual analysis in the measurement stage of evaluation and highlight the demand for computer-support through our system.