Convolutional Recurrent Neural Networks for Dynamic MR Image Reconstruction

5 Dec 2017Chen QinJo SchlemperJose CaballeroAnthony PriceJoseph V. HajnalDaniel Rueckert

Accelerating the data acquisition of dynamic magnetic resonance imaging (MRI) leads to a challenging ill-posed inverse problem, which has received great interest from both the signal processing and machine learning community over the last decades. The key ingredient to the problem is how to exploit the temporal correlation of the MR sequence to resolve the aliasing artefact... (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.