Meeting Banner
Abstract #0382

Deep Learning Reconstruction for Combined 8-fold Accelerated Parallel Imaging and Simultaneous Multislice Acquisition

Mahmoud Mostapha1, Gregor Koerzdoerfer2, Boris Mailhe1, Esther Raithel2, Inge M. Brinkmann2, Nirmal Janardhanan1, Maria Ringholz2, Mariappan S. Nadar1, and Jan Fritz3
1Siemens Healthineers, Princeton, NJ, United States, 2Siemens Healthcare GmbH, Erlangen, Germany, 3Department of Radiology, NYU Grossman School of Medicine, New York, NY, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, MSKCombining parallel imaging (PI) and simultaneous multislice (SMS) acceleration realized a clinical 4-fold accelerated 2D TSE MRI of the knee. However, 8-fold acceleration with conventional reconstruction methods suffers from significant image quality degradation. We propose a complete DL approach for combined slice separation and k-space-to-image reconstruction of SMS-PI-accelerated knee MRI with tunable denoising strength and super-resolution image enhancement. The proposed methods enable artifact-free image reconstruction of 8-fold accelerated 2D TSE MR images in multiple planes and with multiple image contrasts. Clinical evaluations suggest equivalence of image quality and detection rates of 8-fold S2P4 DL reconstructions compared to the reference standard.

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