1 citations · 1 across the 3 of their papers we have counts for
4 papers
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…
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…
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…
GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set
Hanqing Chao, Kun Wang, Yiwei He +2
Gait is a unique biometric feature that can be recognized at a distance; thus, it has broad applications in crime prevention, forensic identification, and social security. To portr…