1University of Queensland, St Lucia, Queensland, Australia; 2The University of Queensland, St Lucia, Queensland, Australia
To more effectively predict the patient SAR values for high-field MRI applications, a novel approach of creating patient-specific tissue model is demonstrated in this study. First, a matching model from a high-resolution image- and tissue-library is selected for the target patient. The library tissue distribution is then warped to match the patients geometry as the corresponding library image is registered to the low-resolution scans of the patient. Results from studying the models 1-gram SAR distribution using finite-different time-domain method suggest that the developed patient model can predict regions of elevated SAR within the patient with remarkable accuracy.