Automatic Vessel Centerline Extraction in Contrast Enhanced Cardiac CT Data

Diplomarbeit

By the introduction of multi-slice computed tomography, computed multislice angiography has become a major non-invasive alternative to conventional angiography for cardiac diagnostic imaging. For the location and analysis of coronary artery disease the main points of interest are the coronary vessels surrounding the myocardium and their primary development. Hence, powerful algorithms have been developed to segment the coronary arteries and extract their centerlines. However, most of the algorithms existing today are semi-automatic, requiring user intervention to create the segmentation result.


In this thesis, a full automatic vessel segmentation and centerline extraction algorithm for coronary artery trees should be developed and an application prototype shall be built. Therefore, existing segmentation and centerline extraction algorithms must be investigated and their adequacy for building the basis of a fully automated extraction algorithm has to be identified. Additionally, the developed algorithm should be able to automatically label the vessel parts been extracted. Finally, the quality of the algorithm has to be evaluated.

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