Alex Bäuerle, member of the research group Visual Computing gives an introdcution of his dissertation topic of the title Visualization Interfaces for Different Stakeholders in the ML Pipeline.
Abstract: Projection techniques are one of the fundamental methods to transform data and make it available to the viewer when it comes to medical visualization. In this context, the type of data involved is spatial, such as CT volumes or ultrasound scans. Modern imaging modalities capture a lot of information, however, not all of it is always of great importance. Medical visualization applications often hide dispensable data and accentuate important details to focus on the individual task at hand. Combining the right information with an effective visual encoding is a difficult challenge. Nevertheless, the goal is to enable an expert to form a well-founded decision, which allows the best possible treatment of a patient.
This dissertation examines projections combined with other forms of effective visualization methods to create novel medical visualization approaches. The here presented work comprises of a survey regarding flattening-based medical visualizations, among several individual visualization techniques for specific applications. Some of the addressed medical procedures in this dissertation have so far not gained a lot of attention. We have also conducted several studies to investigate if our developed approaches successfully support the users with their tasks. Additionally, we introduce a design space for our visualizations to characterize their fundamental composition.
