Diploma and Master Theses (authored and supervised):
"Automated Processing and Visualization of Vessel Trees";
Supervisor: M. Sramek, A. Varchola;
Institut für Computergraphik und Algorithmen,
final examination: 2010-07-25.
Automated processing and visualization of vascular structures is a common task in medical imaging. Maximum Intensity Projection (MIP) and Curved Planar Reformation (CPR) are well established and robust methods for clinical use. In case of calcified vessel walls, occlusion prevents exploring the inside of the vessels when using MIP. CPR allows to cut a single vessel along its centerline and to visualize the lumen. Extending the idea of CPR, a novel automatic method for vessel visualization is proposed. It works with multiple vessel centerlines that do not necessarily need to be connected into a tree structure. Arbitrarily complex vascular structures are rendered in the volume as point sets and optionally, occlusion halos are created around them to enhance depth perception. Vessel centerlines are automatically extracted from a volumetric data-set after performing feature extraction in a scale-space. The user is provided with the ability to control the final image and he or she can visually select the desired centerlines with visual queries by stroking with the mouse. Furthermore, a combination with the recent Maximum Intensity Difference Accumulation (MIDA) visualization technique is presented, which has the advantages of Direct Volume Rendering (DVR) such as occlusion and depth cues, but does not require an explicit transfer function specification. It is demonstrated how the proposed technique can be applied to large data-sets, particularly to data featuring peripheral arterial occlusive diseases or in order to detect possible embolisms as presented on a pulmonary data-set.
Created from the Publication Database of the Vienna University of Technology.