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sEEG-Suite: An Interactive Pipeline for Semi-Automated Contact Localization and Anatomical Labeling with Brainstorm.

Chinmay Chinara1, Raymundo Cassani2, Takfarinas Medani1

  • 1University of Southern California, Los Angeles, USA.

Biorxiv : the Preprint Server for Biology
|September 26, 2025
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Summary

We developed a semi-automatic pipeline for stereoelectroencephalography (sEEG) contact localization and labeling. This tool improves accuracy and efficiency in mapping epileptic networks for better surgical outcomes in drug-resistant epilepsy.

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Area of Science:

  • Neuroscience
  • Medical Imaging
  • Computational Biology

Background:

  • Stereoelectroencephalography (sEEG) is crucial for drug-resistant epilepsy surgery.
  • Accurate sEEG contact localization is vital for identifying the seizure onset zone (SOZ).
  • Manual methods for sEEG contact analysis are error-prone and time-consuming.

Purpose of the Study:

  • To develop and integrate a semi-automatic pipeline for sEEG contact localization and labeling.
  • To enhance the accuracy and efficiency of sEEG data processing.
  • To facilitate reproducible research and clinical workflows in epilepsy surgery.

Main Methods:

  • Co-registration of post-implantation CT with pre-implantation MRI.
  • Semi-automatic detection of sEEG contacts using the GARDEL plugin within Brainstorm.
  • Automatic anatomical labeling of contacts using standard brain atlases.

Main Results:

  • Successful integration of a semi-automatic sEEG contact localization and labeling pipeline into Brainstorm.
  • Demonstration of accurate co-registration, contact detection, and anatomical labeling.
  • Leveraging GARDEL's automation with Brainstorm's multimodal analysis capabilities.

Conclusions:

  • The developed sEEG-Suite tool streamlines sEEG contact analysis.
  • This pipeline enhances reproducibility and accelerates investigations in invasive brain recordings.
  • The tool supports clinical workflows for improved epilepsy surgery planning.