HCC: Medium: Shape Optimization for the Design and Simulation of Electromagnetic Systems

This project aims to create an advanced software tool that automates the design and optimization of electromagnetic (EM) systems, with particular emphasis on magnetic resonance imaging (MRI) an essential medical imaging technology. EM systems are broadly applied and include cell phone antennas, 5G networks, and medical imaging devices. Currently, the design and optimization of these systems are labor-intensive and require a high level of user expertise and interaction. Our software aims to simplify and automate the process. The software will be tested and validated by addressing an open problem in MRI: the optimization of radiofrequency (RF) coil design, a keyl part of MRI machines that significantly impacts the quality of images produced. Current manual optimization processes for RF coils are inefficient and results are suboptimal leading to longer scanning times and lower accuracy. This project will not only make advancements in technology and improve the design process of EM systems, but it also supports interdisciplinary training by involving students from various disciplines. Further, the project holds potential societal benefits in healthcare, cognitive neuroscience, and other sectors that rely on MRI performance. The project's objective is to develop and validate a software pipeline for the shape optimization of EM systems, particularly focusing on automating the forward simulation and the inverse problem of parameter optimization. The proposal combines geometry processing techniques and advanced EM simulations to automate this optimization. The approach will involve novel techniques for differentiable EM simulation, machine learning for acceleration, and shape modeling for automatic geometric variations exploration. The focus of the project will be on RF coil design in MRI machines, particularly those operating at high frequencies (3T and 7T), where existing coil designs only achieve 70-80% of the optimum signal-to-noise ratio. The team will fabricate and test an optimized 7T coil design and compare its performance with commercial RF coils. The project will also introduce an innovative adjoint formulation for efficient shape gradient computation, enabling gradient-based optimization for EM systems with hundreds of design parameters. The results of this project will include an open-source software suite for EM system design and optimization, and it is expected to impact other research projects and contribute to educational and training resources. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.