Real-Time Cardiac Cine MRI with Residual Convolutional Recurrent Neural Network

作者：Eric Z. Chen, Xiao Chen, Jingyuan Lyu, Zheng Yuan, Terrence Chen, Jian Xu, Shanhui Sun · 发表于：arXiv (Cornell University) · 年份：2020 · DOI：10.48550/arxiv.2008.05044 · 被引用次数：5 · 研究领域：Advanced MRI Techniques and Applications、Atomic and Subatomic Physics Research、Medical Imaging Techniques and Applications

Real-time cardiac cine MRI does not require ECG gating in the data acquisition and is more useful for patients who can not hold their breaths or have abnormal heart rhythms. However, to achieve fast image acquisition, real-time cine commonly acquires highly undersampled data, which imposes a significant challenge for MRI image reconstruction. We propose a residual convolutional RNN for real-time cardiac cine reconstruction. To the best of our knowledge, this is the first work applying deep learning approach to Cartesian real-time cardiac cine reconstruction. Based on the evaluation from radiologists, our deep learning model shows superior performance than compressed sensing.