ArticleMagnetic resonance in medicine2025
Physics-guided self-supervised learning: Demonstration for generalized RF pulse design.
Article in Magnetic resonance in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Optimal control of spin systems.Science advances · 2026Review
- SelExNet: A Self-Supervised Physics-Informed Framework for Multi-Channel Joint RF and Gradient Waveform Optimization in 2D Spatially Selective Excitation.Magnetic resonance in medicine · 2026Article
- Optimizing Selective RF Pulses for Enhanced Signal Stability in Turbo Spin Echo Using a Differentiable Extended Phase Graph Model.Magnetic resonance in medicine · 2026Article
- Exact analytical solutions of the Bloch equation for the hyperbolic-secant and chirp pulses.Magnetic resonance in medicine · 2025Article
- Physics-guided self-supervised learning: Demonstration for generalized RF pulse design.Magnetic resonance in medicine · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
purposeTo 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
methodsThe 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,
resultsBoth simulations and experiments show that GPS can design a variety of RF pulses with corresponding profiles that agree well with the target input. Despite these verifications, GPS-designed pulses have unique differences compared to conventional designs, such as achieving
conclusionThis work demonstrates the generalizability, versatility, and flexibility of the GPS method for designing RF pulses and showcases its utility in several applications.
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