Keywords: Software Tools, Software Tools, Extended Phase Graphs
Motivation: Most existing MR simulators either focus on the implementation of multiple physical phenomena or on massive parallelization, but these two aspects are usually not tackled simultaneously.
Goal(s): To provide a feature-rich, massively parallelized and differentiable MR simulator.
Approach: We built on the Extended Phase Graphs formalism to efficiently simulate all the main MR physical phenomena. We used PyTorch as a backend to enable massive parallelization and efficient differentiation.
Results: Our toolbox, demonstrated on a numerical Fast Spin Echo experiment on an exchanging two-pool system, achieved order of magnitude speed-up compared to existing implementations and efficient differentiation with minimal boilerplate.
Impact: Torch-EPG-X will represent a useful tool for synthetic signal generation for deep learning, parameter fitting, model-based reconstruction and sequence optimization.
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