Meeting Banner
Abstract #0351

Stacked UNet-Assisted Joint Estimation for Robust 3D Motion Correction

Brian Nghiem1,2, Zhe Wu2, Lars Kasper2, and Kâmil Uludağ1,2
1Dpt. of Medical Biophysics, University of Toronto, Toronto, ON, Canada, 2University Health Network, Toronto, ON, Canada

Synopsis

Keywords: Motion Correction, Motion CorrectionWe showed that accurate 3D retrospective motion correction of T1w MPRAGE data can be achieved with a UNet-assisted joint estimation algorithm. We compared the proposed method to using the UNet on its own and the standard joint estimation algorithm. Joint estimation (with and without the UNet) outperformed using the stand-alone UNet. The UNet-assisted joint estimation algorithm converged faster than its UNet-free counterpart. We demonstrated the importance of adapting to the changing levels of artifacts over the course of the joint estimation algorithm by sequentially employing different UNets trained for correcting different levels of motion corruption.

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.

Click here for more information on becoming a member.

Keywords