Sustainable MRI: Interpretable Deep Learning for estimating energy and power consumption, revealing key acquisition parameters and their interactions

Magnetic resonance imaging (MRI) is among the most energy-intensive medical imaging modalities. To facilitate the development of more energy-efficient MRI protocols and sequences, we developed an interpretable data-driven deep learning (DL) framework to characterize the factors driving energy and po