Physics-guided self-supervised learning: Demonstration for generalized RF pulse design.

ABSTRACT:

Purpose

To introduce a new method for generalized RF pulse design using physics-guided self-supervised learning (GPS), which uses the Bloch equations as the guiding physics model.

Theory and methods

The GPS framework consists of a neural network module and a physics module, where the physics module is a Bloch simulator for MRI applications. For RF pulse design, the neural network module maps an input target profile to an RF pulse, which is subsequently loaded into the physics module. Through the supervision of the physics module, the neural network module designs an RF pulse corresponding to the target profile. GPS was applied to design 1D selective, B 1 $$ {B}_1 $$ -insensitive, saturation, and multidimensional RF pulses, each conventionally requiring dedicated design a

SUBMITTER: Jang A 

PROVIDER: S-EPMC11604838 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature