16 citations · 20 across the 3 of their papers we have counts for
3 papers
eess.IV2019★ 4 cited
k-t NEXT: Dynamic MR Image Reconstruction Exploiting Spatio-temporal Correlations
Chen Qin, Jo Schlemper, Jinming Duan +4
Dynamic magnetic resonance imaging (MRI) exhibits high correlations in k-space and time. In order to accelerate the dynamic MR imaging and to exploit k-t correlations from highly u…
eess.IV2019★ 16 cited
VS-Net: Variable splitting network for accelerated parallel MRI reconstruction
Jinming Duan, Jo Schlemper, Chen Qin +7
In this work, we propose a deep learning approach for parallel magnetic resonance imaging (MRI) reconstruction, termed a variable splitting network (VS-Net), for an efficient, high…
cs.CV2017
A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction
Jo Schlemper, Jose Caballero, Joseph V. Hajnal +2
The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from under…