Multi-coil magnetic resonance imaging using deep learning

A magnetic resonance imaging (MRI) system, comprising:

• a magnetics system having a plurality of magnetics components to produce magnetic fields for performing MRI, the magnetics system comprising:
• a plurality of RF coils configured to detect MR signals;
• and
• at least one permanent B0 magnet configured to produce a B0 field for an imaging region of the MRI system, the B0 field having a strength between 50 milliTesla and 100 milliTesla;
• and
• at least one processor configured to perform:
• obtaining a plurality of input MR datasets obtained by the MRI system to image a subject, each of the plurality of input MR datasets comprising spatial frequency data and obtained using a respective RF coil in the plurality of RF coils;
• generating a respective plurality of MR images from the plurality of input MR datasets by using an MR image reconstruction technique;
• estimating, using a neural network model, a plurality of RF coil profiles corresponding to the plurality of RF coils;
• generating an MR image of the subject using the plurality of MR images and the plurality of RF coil profiles;
• and
• outputting the generated MR image.

At least one non-transitory computer readable storage medium storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to perform a method for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system having a plurality of RF coils configured to detect MR signals, the method comprising:

• obtaining a plurality of input MR datasets obtained by the MRI system to image a subject, each of the plurality of input MR datasets comprising spatial frequency data and obtained using a respective RF coil in the plurality of RF coils, wherein the MRI system comprises at least 8 RF coils and the plurality of input MR datasets comprises at least 8 input MR datasets;
• generating a respective plurality of MR images from the plurality of input MR datasets by using an MR image reconstruction technique;
• estimating, using a neural network model, a plurality of RF coil profiles corresponding to the plurality of RF coils;
• generating an MR image of the subject using the plurality of MR images and the plurality of RF coil profiles;
• and
• outputting the generated MR image.