Deep learning is an effective image processing approach that has been enthusiastically adopted in Magnetic Resonance Spectroscopy (MRS). Methods such as multilayer perceptrons (MLP) and convolutional neural networks (CNN) have been applied to frequency and phase correction (FPC) to help resolve frequency and phase shifts that arise in MRS. However, both methods need to be trained separately with frequency and phase offsets to perform FPC. In this study, we aim to introduce a spectrum registration technique using CNNs that perform simultaneous correction of both frequency and phase shifts of single voxel MEGA-PRESS MRS simulated data.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords