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Real-time visualization for transcranial magnetic stimulation (TMS)
- Loraine Franke (University of Massachusetts Boston)
- Jax Luo (BWH & Harvard Medical School)
- Raymond Yang (University of Massachusetts Boston)
- Lipeng Ning (BWH & Harvard Medical School)
- Steve Pieper (Isomics, Inc.)
- Daniel Haehn (University of Massachusetts Boston)
Transcranial magnetic stimulation is a nonivasive procedure used for treating depression with magnetic and electric fields to stimulate nerve cells.
A TMS coil is slowly moved over the subject’s head suface to target certain areas in the brain.
Our project aims to develop a deep-learning powered software for real-time E-Field prediction and a visualization of TMS within 3D Slicer.
Real-time visualization of an electric field (E-field) for transcranial magnetic stimulation (TMS) on the brain surface, visualization through an AR app (over browser).
Approach and Plan
- We created a TMS module in Slicer mapping NifTi file onto brain mesh with 3D TMS coil that can be moved by the user (done) -> TODO: create a bounding box for the Coil mesh to not turn it into brain, attach the coil to the skull/skin surface
- We use OpenIGTLinkIF used to transfer data (E-Field from TMS) into 3D Slicer (done)
- Next steps include connecting 3DSlicer to the web browser using our newly implemented WebSocket from https://github.com/liampaulhus/slicerWebWSS-WIP
Progress and Next Steps
- Some bug fixes of observers in the TMS Module
- Integration of deep learning model: Modified OpenIGTLink with pyigtl (https://github.com/lassoan/pyigtl) to send out transform message of the moving TMS coil (added nodes, enabled push on connect, modified python demon that accesses the outgoing data), in collaboration with the deep learning project Slicer TMS Deep-Learning
- Tested our new secure websocket connection to the browser (https://github.com/liampaulhus/slicerWebWSS-WIP) using a self-signed certificate for https.
- Next steps: a) Attach the coil to the skull/skin surface in Slicer and b) Modify the browser-based WebXR controller so that it can be synchronized with slicer
Current Visualization of the TMS Module in 3DSlicer with Coil and mapping of E-field on brain:
Coil moving and updating the electric field on the brain surface inside slicer:
Started WebSocket Tests: we can interact with the red, green and yellow slices with the new websocket connection:
Background and References
This project is related to: ../SlicerTMS_E-field
Infos for running WebXR:
Phones need a Depth sensor to run AR/VR. A list of supported devices can be found here: https://developers.google.com/ar/devices
On an Android Phone via USB:
- PlayStore: Download Google VR Services and Google AR Services App
- Update Chrome/Camera apps etc.
- On the phone: Enable Developer tools (https://developer.android.com/studio/debug/dev-options) and USB debugging (description here: https://developer.chrome.com/docs/devtools/remote-debugging/)
- Run chrome://inspect#devices in the browser on your computer and it should detect USB connected devices
- Mozilla offers a WebXR Emulator that can be downloaded from the Apple Store for any iPhone and iPad: https://labs.mozilla.org/projects/webxr-viewer/
For Slicer TMS Module (see previous project week PW 36):
<!– vtkProbeFilter: https://vtk.org/doc/nightly/html/classvtkProbeFilter.html
Moving fiducials with CPYY: https://gist.github.com/pieper/f9da3e0a73c70981b48d0747132526d5
Measure rendering time in 3D Slicer:
- Getting renderer: https://slicer.readthedocs.io/en/latest/developer_guide/script_repository.html#access-vtk-views-renderers-and-cameras
- Then applying renderer.GetLastRenderTimeInSeconds()