2025-07-23 –, Main Room 3
KomaMRI.jl is a tool developed to efficiently simulate the physics of magnetic resonance phenomena by solving the Bloch equations, helping to address technical challenges that can affect medical image quality. These simulations are especially useful for designing pulse sequences, a fundamental component of MRI acquisition. In this talk, I will present recent technical developments that make the tool more versatile and broadly applicable.
KomaMRI.jl is a tool developed to efficiently simulate the physics of magnetic resonance phenomena by solving the Bloch equations, helping to address technical challenges that can affect medical image quality. These simulations are especially useful for designing pulse sequences, a fundamental component of MRI acquisition. KomaMRI.jl is part of the JuliaHealth GitHub organization and is currently its most starred package, reflecting its strong reception within both the Julia and MRI communities. It was featured as a 30-minute oral presentation at JuliaCon 2023, and its associated paper was among the top 10 percent most viewed articles in Magnetic Resonance in Medicine.
In this talk, I will present recent technical developments that make the tool more versatile and broadly applicable. These include optimized GPU kernels for faster simulations, vendor-agnostic GPU acceleration (now supporting Metal.jl, oneAPI.jl, and AMDGPU.jl), support for distributed computing, and the ability to model complex motion in the simulated object, which is particularly important for cardiac imaging. I will also share preliminary results on integrating KomaMRI.jl with AD frameworks to optimize pulse sequence design and tackle other inverse problems, such as image reconstruction.
Carlos Castillo-Passi began his academic journey at Pontificia Universidad Catolica de Chile (PUC), where he earned both a degree and an MSc in Electrical Engineering in 2018. He then pursued a PhD in Biological and Medical Engineering through a joint program between PUC and King’s College London (KCL), completing it with maximum distinction in 2024. His research focused on the design of low-field cardiac MRI sequences using open-source MRI simulations. In 2023, his work on open-source MRI simulations was highlighted by the editor of Magnetic Resonance in Medicine (MRM). Furthermore, his application of this work to low-field cardiac MRI earned him the Early Career Award in Basic Science from the Society for Cardiovascular Magnetic Resonance (SCMR) in 2024. In addition to his research, Carlos is an active member of JuliaHealth, contributing to the development of high-performance, reproducible tools for health and medicine. In 2025, he joined Stanford University as a postdoctoral researcher, where he continues his work in cardiac MRI and open-source technologies.