Deep learning (DL) has recently become a promising technique to address the safety concerns for Gadolinium-based Contrast Agents (GBCAs) in MRI. Studies have shown that high quality contrast-enhanced images can be generated by DL with only a small fraction of the standard dose, and in some cases no dose at all. To build upon existing research that has heavily focused on qualitative evaluation by radiologists, this work proposes an automated quantitative evaluation scheme for the GBCA dose reduction using DL.
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