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eess.IV2026
Sustainable MRI: Interpretable Deep Learning for estimating energy and power consumption, revealing key acquisition parameters and their interactions
Florian Leonhard Raab, Fiona Mankertz, Nour Maalouf +16
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,…
eess.IV2026
Towards a Unified Theoretical Framework for Splitting-based Self-Supervised MRI Reconstruction
Siying Xu, Kerstin Hammernik, Daniel Rueckert +2
The demand for high-resolution, non-invasive imaging continues to drive innovation in magnetic resonance imaging (MRI), but long acquisition times remain a major practical limitati…