The main goal of this thesis was to develop methods for automated segmentation, registration and classification of the carotid artery vessel wall and plaque components using multi-sequence MR... Show moreThe main goal of this thesis was to develop methods for automated segmentation, registration and classification of the carotid artery vessel wall and plaque components using multi-sequence MR vessel wall images to assess atherosclerosis. First, a general introduction into atherosclerosis and different stages of the disease were described including the importance to differentiate between stable and vulnerable plaques. Several non-invasive imaging techniques were discussed and the advantages of multi-sequence MRI were highlighted. Different novel automated image segmentation and registration techniques for analysis of the MRI images have been developed. A 3D vessel model to automatically segment the vessel wall was presented. Automated image registration was applied to correct for patient movement during the acquisition of an MRI scan and between MRI scans. The last topic is the automatic classification of the different plaque components which can be present inside the vessel wall. All techniques were developed and validated using relevant patient data and reference standards. The work presented is an important contribution to the automated analysis of multi-sequence MR vessel wall imaging of the carotid artery. These techniques can speed up the current manual analysis and are potentially more accurate and more reproducible. Show less
