Efficient Local SAR Prediction Based on Anatomical Differences and Model Order Reduction

Abstract

An efficient approach to local SAR prediction is presented based on anatomical differences and model order reduction, which substantially reduces the memory footprint of this framework. The reduced order model can be solved using a direct inverse, which allows solving for the RF fields for multiple transmit channels simultaneously, which significantly improves the scalability in view of upcoming high field systems with an increasing number of RF transmit channels.