599 citations · 753 across the 15 of their papers we have counts for
17 papers
Towards Sustainable Magnetic Resonance Imaging: Insights from long-term, high-resolution energy recordings across an entire scanner fleet
Florian Leonhard Raab, Fiona Mankertz, Nour Maalouf +17
Magnetic resonance imaging (MRI) is among the most energy-intensive diagnostic modalities in healthcare, yet its energy consumption and the factors influencing it remain insufficie…
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,…
The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization
Jakob Dexl, Katharina Jeblick, Andreas Mittermeier +27
We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body PET/CT under a compositional generaliza…
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…
MIMM-X: Disentangling Spurious Correlations for Medical Image Analysis
Louisa Fay, Hajer Reguigui, Bin Yang +2
Deep learning models can excel on medical tasks, yet often experience spurious correlations, known as shortcut learning, leading to poor generalization in new environments. Particu…
CUTE-MRI: Conformalized Uncertainty-based framework for Time-adaptivE MRI
Paul Fischer, Jan Nikolas Morshuis, Thomas Küstner +1
Magnetic Resonance Imaging (MRI) offers unparalleled soft-tissue contrast but is fundamentally limited by long acquisition times. While deep learning-based accelerated MRI can dram…