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，这在针对特定患者脑区实施干预时尤为困难。计算最佳线圈位置及其在脑表面产生的电场既昂贵又耗时。我们提出SlicerTMS这一模拟方法，可在医学成像平台3D Slicer中实现对TMS电磁场的实时可视化。本软件采用三维深度神经网络，支持云端推理，并通过WebXR实现增强现实可视化。我们评估了SlicerTMS在多种硬件配置下的性能，并将其与现有TMS可视化应用SimNIBS进行了对比。所有代码、数据和实验均公开可获取：\url{https://github.com/lorifranke/SlicerTMS}