TY  - THES
T1  - Computer Aided Diagnosis Methods for Coronary CT Angiography
A1  - Teßmann,Matthias
Y1  - 2011/05/03
N2  - Cardiovascular diseases are the number one cause of death in the world. As a consequence, cardiovascular diseases are a major health and economic problem. Any actions taken to support the clinical process during diagnosis, treatment and aftercare procedures are therefore strongly desirable. Today medical imaging techniques play a key role for this purpose. Especially cardiac imaging has high demands on the imaging modality with respect to spatial and temporal resolution. The image quality that can be acquired by computed tomography is almost at pace with traditional catheter based an- giography. However, analysis of the data is a manual and time consuming process. Hence, a quick evaluation of the images is required in order to provide optimal patient care. Especially the identification of small structures like plaques contained in the coronary arteries of the heart is difficult. In this thesis, methods were examined that approach this problem. The foundation of the presented algorithms is a robust segmentation of the coronary arteries within the data. Based on this segmentation, methods that operate on its results have been developed that allow the classification of pathologies along the vessels. A learning-based approach has been implemented and used to identify diseased regions along the arteries. The resulting algorithm is capable of quickly detecting the location of soft- and calcified plaques in the data. Besides the detection of the location and the type of plaques, their quantification is important with respect to risk assessment. A fully automatic, threshold based segmentation and scoring method for calcified plaque is presented that delivers similar results than those obtained by manual segmentation from a radiologist. Finally, a snake-based segmentation algorithm for soft-plaques in CT angiography data has been examined. This approach generates a boundary hull along the whole vessel and extracts a radius distribution curve from that data. Thereby, it is possible to detect and quantify the narrowing of vessel lumen in the presence of a soft-plaque.
Overall, the algorithms presented in this thesis and the software products that were developed in conjunction with it could contribute significantly to the provision and improvement of computer aided diagnostic methods for the analysis of coronary artery disease in CT data.
KW  - Bildverarbeitung
KW  - Spiral-CT
KW  - Computertomographie
KW  - Segmentierung
KW  - Diagnose
KW  - Koronare Herzkrankheit
KW  - Computergraphik
KW  - Visualisierung
CY  - Erlangen
PB  - Universitätsbibliothek der Universität Erlangen-Nürnberg
AD  - Universitätsstraße. 4, 91054 Erlangen
L2  - http://www.opus.ub.uni-erlangen.de/opus/volltexte/2011/2497
ER  -