Meeting Banner
Abstract #3109

A data-driven approach to accelerate IR-prepared UTE Bone Imaging of the Knee

Philipp Hans Nunn1, Oliver Schad1, Henner Huflage1, Jan-Peter Grunz1,2, Thorsten Alexander Bley1, Johannes Tran-Gia3, and Tobias Wech1,4
1Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 2Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany, 4Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany

Synopsis

Keywords: Bone/Skeletal, Bone

Motivation: (IR)-UTE MRI allows for (quantitative) assessment of bony tissue. However, imaging often suffers from poor SNR and time-consuming protocols.

Goal(s): To develop a reconstruction method that can transfer undersampled IR-UTE-based scans of the knee into high-quality images.

Approach: A physics-based reconstruction algorithm was implemented, which incorporates a denoising convolutional neural network (DnCNN) specifically trained for the presented application.

Results: Exploiting the tailored DnCNN within the iterative reconstruction algorithm leads to significant noise suppression and an overall improved image quality compared to incorporating a generic DnCNN or applying the networks alone.

Impact: The proposed reconstruction technique demonstrates potential for MR-based assessment of osseous tissue within clinically appealing 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.

Click here for more information on becoming a member.

Keywords