Diploma and Master Theses (authored and supervised):

L. Pezenka:
"Brain Biopsy Planning using Multi-Dimensional Data";
Supervisor: E. Gröller; Institut für Computergraphik und Algorithmen, 2017; final examination: 2017-11-28.

English abstract:
safety margins, the avoidance of risk structures, trajectory length and trajectory angle
into consideration. While some of those factors are mandatory, others can be optimized
in order to obtain the best possible trajectory under the given circumstances. Through
comparison with the actually chosen trajectories from real biopsies and qualitative
interviews with domain experts, we identified important rules for trajectory planning.
In this thesis, we present BrainXplore, an interactive visual analysis tool for aiding
neurosurgeons in planning brain biopsies. BrainXplore is an extendable Biopsy
Planning framework that incorporates those rules while at the same time leaving full
flexibility for their customization and adding of new structures at risk. Automatically
computed candidate trajectories can be incrementally refined in an interactive manner
until an optimal trajectory is found. We employ a spatial index server as part of our
system that allows us to access distance information on an unlimited number of risk
structures at arbitrary resolution. Furthermore, we implemented InfoVis techniques such
as Parallel Coordinates and risk signature charts to drive the decision process. As a case
study, BrainXPlore offers a variety of information visualization modalities to present
multivariate data in different ways.
We evaluated BrainXPlore on a real dataset and accomplished acceptable results. The
participating neurosurgeon gave us the feedback that BrainXPlore can decrease the
time needed for biopsy planning and aid novice users in their decision making process.

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.