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

翻译：经颅磁刺激（TMS）是一种非侵入性神经调控方法，可有效治疗多种脑部疾病。TMS治疗成功的关键因素之一是精确的线圈定位，而这一过程在针对特定患者脑区进行靶向时颇具挑战性。计算最优线圈放置位置及其在脑表面产生的电场往往成本高昂且耗时。我们提出SlicerTMS——一种能够在医学影像平台3D Slicer中实现TMS电磁场实时可视化的仿真方法。该软件基于三维深度神经网络，支持云端推理，并通过WebXR实现增强现实可视化。我们针对多种硬件配置评估了SlicerTMS的性能，并与现有TMS可视化应用SimNIBS进行了对比分析。所有代码、数据及实验均开源提供：\url{https://github.com/lorifranke/SlicerTMS}