The high sensitivity of MRI at 7T enables brain imaging with unprecedented spatial resolution, which can be important to the assessment of a variety of neurological disorders, such as multiple sclerosis, epilepsy, and neurodegenerative disease. With sub-millimeter voxel dimensions, and prolonged acquisition times, however, sensitivity to motion and pulsatility is increased dramatically. This increased sensitivity to motion can be managed with techniques like PROPELLER. Here, we present an initial assessment of a deep learning-based image reconstruction for high-resolution, 7T PROPELLER, and evaluate its ability to improve signal-to-noise ratio, and anatomical conspicuity, without increasing scan time.
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