A crucial safety concern for UHF MRI is the significant RF power deposition in the body in the form of local specific absorption rate (SAR) hotspots, leading to dangerous tissue heating/damage. This work is a proof-of-concept demonstration of an artificial intelligence (AI) based real-time MRI safety prediction software (MRSaiFE) facilitating safe generation of 3T and 7T images by means of accurate local SAR-monitoring at sub-W/kg levels. This feasibility study demonstrates that SAR patterns can be predicted with a root-mean-square error (RMSE) of <11% along with a structural similarity (SSIM) level of >84% for both field strengths.
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