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

arXiv: https://arxiv.org/abs/2008.05044 · HTML: https://mlsanity.com/paper/2008.05044/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2020.

## Built on by (most cited first, 2 of 2)

- [Holistic Multi-Slice Framework for Dynamic Simultaneous Multi-Slice MRI Reconstruction](https://mlsanity.com/paper/2301.01355/) (2023)
- [Cardiac Functional Analysis with Cine MRI via Deep Learning Reconstruction](https://mlsanity.com/paper/2105.08157/) (2021)

## Abstract (arXiv)

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.