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eess.IV2025
Improving Deep Learning for Accelerated MRI With Data Filtering
Kang Lin, Anselm Krainovic, Kun Wang +1
Deep neural networks achieve state-of-the-art results for accelerated MRI reconstruction. Most research on deep learning based imaging focuses on improving neural network architect…
eess.IV2025
Reliable Evaluation of MRI Motion Correction: Dataset and Insights
Kun Wang, Tobit Klug, Stefan Ruschke +2
Correcting motion artifacts in MRI is important, as they can hinder accurate diagnosis. However, evaluating deep learning-based and classical motion correction methods remains fund…
eess.IV2024
MotionTTT: 2D Test-Time-Training Motion Estimation for 3D Motion Corrected MRI
Tobit Klug, Kun Wang, Stefan Ruschke +1
A major challenge of the long measurement times in magnetic resonance imaging (MRI), an important medical imaging technology, is that patients may move during data acquisition. Thi…