Meeting Banner
Abstract #2772

Stepwise hard constraint-biased Physics-informed Neural Networks for accurate Magnetic Resonance Electrical Properties Tomography (MREPT)

Ruian Qin1, Junqi Yang1, Zhongchao Zhou1, Jose Gomez-Tames1,2, Shaoying Huang3,4, and Wenwei Yu1,2
1Department of Medical Engineering, Chiba University, Chiba, Japan, 2Center for Frontier Medical Engineering, Chiba University, Chiba, Japan, 3Department of Surgery, National University of Singapore, Singapore, Singapore, 4Engineering Product Development Department, Singapore University of Technology and Design, Singapore, Singapore

Synopsis

Keywords: AI/ML Image Reconstruction, Electromagnetic Tissue Properties

Motivation: MREPT faces challenges with insufficient constraints and bias when integrated with Physics-informed Neural Networks (PINN), impacting its accuracy.

Goal(s): We aim to use only physics-based constraint to bias well-used numerical MREPT methods to enhance the PINN.

Approach: We sequentially applied a Stabilized-EPT (Stab-EPT)-based supervised-learning, a biased-Convention-Reaction-EPT (CR-EPT)-based PINN. This stepwise process grounds and balances the multiple-terms in the partial differentiation equation of CR-EPT during learning, thus helps avoid local minima.

Results: The proposed PINN approach shows the possibility to outperform Stab-EPT with improved SSIM and NRMSE, though stop criterion needs to be investigated. Further tuning of the bias might improve MREPT accuracy.

Impact: This stepwise constraint-biased PINN approach could enable accurate MREPT without any ground truth, thus represent a step forward for clinical application of MREPT.

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