DeepECG: Towards 3-D Continuous Cardiac MRI without ECG-Gating - Deep Learning-based R-Wave Classification for Automated Cardiac Phase Binning

For continuous cardiac CINE acquisitions, cardiac binning of the data is necessary, which is done either using ECG-gating or hand-crafted postprocessing methods. To overcome these limitations, we propose a deep learning classifier to detect R-waves from repeated 1-D superior-inferior projections of the imaged data. After training with R-wave positions from the ECG signal as ground-truth data, detection of R-waves is possible without additional ECG-gating or hand-crafted features and can be used for retrospective cardiac binning. Our first proof-of-concept achieves a high accuracy of over 91% on previously unseen cardiac CINE data.