CNN-based Off-resonance Correction in Cardiac Spiral MRI
Shishuai Wang1, Pedro F Ferreira2, Zohya Khalique2, Margarita Gorodezky2, Malte Roehl2, Jialin Pu3, Dudley J Pennell2, Sonia Nielles-Vallespin2, and Andrew D Scott2
1Department of Physics, Imperial College London, London, United Kingdom, 2Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital and National Heart and Lung Institute, Imperial College London, London, United Kingdom, 3College of Information And Communication Engineering, Harbin Engineering University, Harbin, China
Spiral trajectories are time efficient but are susceptible to off-resonance artefacts. Many approaches to off-resonance correction require a high-quality B0 field map. Here we train a convolutional neural network to remove the off-resonance artefacts using simulated cardiac spiral MRI and validate our methods by applying this network to diffusion tensor cardiovascular MR (DTCMR) data acquired with spiral trajectories.
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