Rethinking the optimization process for self-supervised model-driven MRI reconstruction

W Huang, C Li, W Fan, Z Zhang, T Zhang… - … Workshop on Machine …, 2022 - Springer
Recovering high-quality images from undersampled measurements is critical for accelerated
MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction …
被引用次数：3 相关文章

Rethinking the optimization process for self-supervised model-driven MRI reconstruction

W Huang, C Li, W Fan, Y Zhou, Q Liu, H Zheng… - arXiv e …, 2022 - ui.adsabs.harvard.edu
Recovering high-quality images from undersampled measurements is critical for accelerated
MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction …

Rethinking the optimization process for self-supervised model-driven MRI reconstruction

W Huang, C Li, W Fan, Y Zhou, Q Liu, H Zheng… - arXiv preprint arXiv …, 2022 - arxiv.org
Recovering high-quality images from undersampled measurements is critical for accelerated
MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction …

Rethinking the Optimization Process for Self-supervised Model-Driven MRI Reconstruction

Y Zhou, Q Liu, S Wang - Machine Learning for Medical Image Reconstruction - Springer
Recovering high-quality images from undersampled measurements is critical for accelerated
MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction …

Rethinking the Optimization Process for Self-supervised Model-Driven MRI Reconstruction

W Huang, C Li, W Fan, Z Zhang, T Zhang… - … Workshop on Machine …, 2022 - dl.acm.org
Recovering high-quality images from undersampled measurements is critical for accelerated
MRI reconstruction. Recently, various supervised deep learning-based MRI reconstruction …