NA-MIC Project Weeks

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Improvements of SlicerTMS

Key Investigators

• Lipeng Ning (Brigham and Women's Hospital and Harvard Medical School, USA)
• Steve Pieper (Isomics Inc., USA)
• Tae Young Park (TruAbutment Inc., USA)
• Daniel Haehn (University of Massachusetts Boston, USA)
• Benjamin Zwick (The University of Western Australia, Australia)
• Satya Barak (The University of Western Australia, Australia)
• Cameron Paterson (The University of Western Australia, Australia)

Project Description

The SlicerTMS project has been developed to predict the electric field induced by transcranial magnetic stimulation by using deep neural networks and magnetic resonance imaging data. In this project week, we further develop the software to improve the performance and integrate additional functions into this module.

Objective

1. Objective A. Improve the overall software architecture for integration with other electric field solvers.
2. Objective B. Develop and test an example on the integration of the SimNIBS solver.
3. Objective C. Validate and update the sampling algorithms in SlicerTMS and improve the file I/O strategy for vector nifti files.
4. Objective D. Discuss and improve the integration with neuronavigation and other fast segmentation and meshing techniques.
5. Objective E. Investigate the use of markerless tracking of the patient head and TMS probe for neuronavigation.

Approach and Plan

1. Meet to review existing SlicerTMS software structure and other external solvers (e.g., SimNIBS).
2. Discuss and prototype an improved architecture.
3. Compare the vtk-based resampling with SimNIBS to improve the accuracy of SlicerTMS models.
4. Talk with other teams about related toolboxes, e.g., OpenIGTLink, for improvement.

Progress and Next Steps

TBD

Illustrations

No response

Background and References

• SlicerTMS GitHub Repository
• 3D Slicer
• Real-Time Visualization of TMS-evoked Potentials PW 40 Project