Deep learning techniques for suppressing artefacts in magnetic resonance images

A magnetic resonance imaging (MRI) system, comprising:

• at least one radio-frequency (RF) coil;
• and
• at least one processor configured to:
• obtain input magnetic resonance (MR) data using the at least one RF coil;
• and
• generate an MR image from the input MR data at least in part by using a neural network model to suppress artefacts in the input MR data, comprising:
• performing a reconstruction step by generating an image in an image domain from the input MR data;
• using a first neural network portion to suppress the a first type of artefact in the input MR data in a domain other than the image domain before the reconstruction step;
• and
• using a second neural network portion to suppress a second type of artefact in the input MR data in the domain other than the image domain before the reconstruction step.