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SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning
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 ind...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246060/ https://www.ncbi.nlm.nih.gov/pubmed/37292474 |
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author | Franke, Loraine Park, Tae Young Luo, Jie Rathi, Yogesh Pieper, Steve Ning, Lipeng Haehn, Daniel |
author_facet | Franke, Loraine Park, Tae Young Luo, Jie Rathi, Yogesh Pieper, Steve Ning, Lipeng Haehn, Daniel |
author_sort | Franke, Loraine |
collection | PubMed |
description | 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: https://github.com/lorifranke/SlicerTMS |
format | Online Article Text |
id | pubmed-10246060 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-102460602023-06-08 SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning Franke, Loraine Park, Tae Young Luo, Jie Rathi, Yogesh Pieper, Steve Ning, Lipeng Haehn, Daniel ArXiv Article 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: https://github.com/lorifranke/SlicerTMS Cornell University 2023-05-23 /pmc/articles/PMC10246060/ /pubmed/37292474 Text en https://creativecommons.org/licenses/by-sa/4.0/This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms. |
spellingShingle | Article Franke, Loraine Park, Tae Young Luo, Jie Rathi, Yogesh Pieper, Steve Ning, Lipeng Haehn, Daniel SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title | SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title_full | SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title_fullStr | SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title_full_unstemmed | SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title_short | SlicerTMS: Interactive Real-time Visualization of Transcranial Magnetic Stimulation using Augmented Reality and Deep Learning |
title_sort | slicertms: interactive real-time visualization of transcranial magnetic stimulation using augmented reality and deep learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246060/ https://www.ncbi.nlm.nih.gov/pubmed/37292474 |
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