Efficient Semiautomatic Segmentation of 3D Objects in Medical Images
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
CoViCAD: Comprehensive Visualization of Coronary Artery Disease
IEEE Transactions on Visualization and Computer Graphics
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
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Non-invasive imaging techniques become more and more important as diagnostic tools for the assessment of coronary heart disease (CHD). While CT is widely applied for the inspection of the coronary arteries, the state of myocardial tissue is normally analyzed with MRI or nuclear imaging methods such as PET or SPECT. The effect of late enhancement, the accumulation of contrast agent in defective tissue, is used to assess tissue viability with MR imaging. Studies have shown, that this effect can be observed for iodine based contrast agents, which are used for CT coronary artery imaging, as well. Thus the goal of this work is the development of segmentation and visualization methods, which allow a combined inspection of the coronary arteries and the viability of the corresponding myocardial tissue. We therefore present a new segmentation method for the analysis of CT late enhancement images and the integration with methods for the inspection of the coronary arteries. In preliminary tests by a radiologist, the methods are applied to 4 datasets to compare the segmentation with the reference method, test the combined inspection for data with a known relation between infarction and supplying artery and test the general applicability to patient data. The preliminary results are promising, and further studies will focus on the evaluation of the segmentation method as well as on the clinical benefit through the combined analysis.