Keywords: Non-Proton, Non-Proton, Super-resolution, fingerprinting
Motivation: To improve resolution for translating sodium MRI into clinical practice.
Goal(s): Develop a super-resolution neural network for brain sodium images.
Approach: A cascaded Y-Net is proposed to generate high-resolution sodium images from simultaneously acquired 1H MRF/23Na MRI data. Human brain images from 8 healthy subjects were used for training and validation (154), and testing (22).
Results: The generated high-resolution sodium images from the Y-Net showed a structural similarity index measure (SSIM) of 0.935, a RMSE=0.034 and a PSNR=28.8 compared with the ground truth.
Impact: We introduce a Y-Net super-resolution neural network that generates high-resolution sodium images from simultaneously acquired 1H MRF/23Na MRI 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