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。影响TMS治疗效果的关键因素之一是线圈的准确定位，尤其在针对特定患者脑区进行靶向刺激时颇具挑战性。计算最优线圈放置位置及其在脑表面产生的电场分布通常成本高昂且耗时。我们提出SlicerTMS——一种在医学影像平台3D Slicer内实现TMS电磁场实时可视化的仿真方法。该软件采用三维深度神经网络架构，支持云推理，并通过WebXR技术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。所有代码、数据及实验均已在开放平台公开：\url{https://github.com/lorifranke/SlicerTMS}