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Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulationapproach that effectively treats various brain disorders. One of the criticalfactors in the success of TMS treatment is accurate coil placement, which canbe challenging, especially when targeting specific brain areas for individualpatients. Calculating the optimal coil placement and the resulting electricfield on the brain surface can be expensive and time-consuming. We introduceSlicerTMS, a simulation method that allows the real-time visualization of theTMS electromagnetic field within the medical imaging platform 3D Slicer. Oursoftware leverages a 3D deep neural network, supports cloud-based inference,and includes augmented reality visualization using WebXR. We evaluate theperformance of SlicerTMS with multiple hardware configurations and compare itagainst the existing TMS visualization application SimNIBS. All our code, data,and experiments are openly available:\url{https://github.com/lorifranke/SlicerTMS}

SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning