8 citations · 12 across the 2 of their papers we have counts for
3 papers
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.IV2023★ 4 cited
Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
Kang Lin, Reinhard Heckel
Deep learning based methods for image reconstruction are state-of-the-art for a variety of imaging tasks. However, neural networks often perform worse if the training data differs…
cs.CV2022★ 8 cited
Image-to-Image MLP-mixer for Image Reconstruction
Youssef Mansour, Kang Lin, Reinhard Heckel
Neural networks are highly effective tools for image reconstruction problems such as denoising and compressive sensing. To date, neural networks for image reconstruction are almost…