Conventional QSM reconstruction algorithms impose long computation time, which inhibits their adoption for real-time clinical use. In this work, we propose a method that replaces conventional iterative algorithms for background removal and dipole inversion with two deep neural networks. The reconstruction results demonstrate comparable performance to the previous outcomes while the new method takes only 3 seconds (up to 106 times faster!), which is unparalleled to conventional methods.
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