29 March 2007 Novel methods for parameter-based analysis of myocardial tissue in MR images
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Abstract
The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.
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A. Hennemuth, A. Hennemuth, S. Behrens, S. Behrens, C. Kuehnel, C. Kuehnel, S. Oeltze, S. Oeltze, O. Konrad, O. Konrad, H.-O. Peitgen, H.-O. Peitgen, "Novel methods for parameter-based analysis of myocardial tissue in MR images", Proc. SPIE 6511, Medical Imaging 2007: Physiology, Function, and Structure from Medical Images, 65111N (29 March 2007); doi: 10.1117/12.710386; https://doi.org/10.1117/12.710386
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