slicer-robotms-neuro-navigation

name	slicer-robotms-neuro-navigation
description	Open-source 3D Slicer extension for robot-assisted transcranial magnetic stimulation (Robo-TMS). Enables accurate, reproducible non-invasive brain stimulation with image-guided robotic intervention. Activation: robot TMS, Robo-TMS, Slicer extension, TMS navigation, transcranial magnetic stimulation robot, neurostimulation robotic.

SlicerRoboTMS: Robot-Assisted TMS Navigation

An open-source 3D Slicer extension that enables robot-assisted transcranial magnetic stimulation, combining image guidance with robotic precision for accurate and reproducible non-invasive brain stimulation.

Metadata

• Source: arXiv:2604.25661v1
• Published: 2026-04-28
• Category: Neurostimulation / Robotic Intervention

Core Methodology

Key Innovation

SlicerRoboTMS bridges the gap between conventional manual TMS and fully automated robotic systems by providing an open-source, extensible platform built on the widely-used 3D Slicer medical imaging software. This enables clinical researchers to implement robot-assisted TMS without proprietary vendor lock-in.

Technical Framework

Robot-Assisted TMS (Robo-TMS)

• Image-guided intervention: Uses MRI/CT data for precise coil positioning
• Robotic accuracy: Sub-millimeter precision for coil placement
• Reproducibility: Eliminates inter-operator variability
• Real-time tracking: Continuous position verification during stimulation

3D Slicer Integration

• Modular architecture: Leverages 3D Slicer's plugin ecosystem
• Multi-modal imaging: Supports MRI, CT, fMRI navigation
• Visualization: Real-time 3D visualization of coil-brain relationship
• Open-source: Extensible and customizable for research needs

Clinical Applications

Standard TMS Targets

• Dorsolateral prefrontal cortex (DLPFC): Depression treatment
• Motor cortex: Motor evoked potential (MEP) studies
• Visual cortex: Phosphene threshold mapping
• Language areas: Pre-surgical language mapping

Research Applications

• Connectivity mapping: TMS-fMRI integration
• Plasticity studies: Paired associative stimulation
• Cognitive modulation: Working memory, attention studies
• Rehabilitation: Post-stroke motor recovery

Implementation Guide

Prerequisites

• Hardware:
  • Compatible robotic arm (e.g., Kinova, Franka, Universal Robots)
  • TMS coil with tracking markers
  • Optical tracking system (e.g., NDI Polaris, OptiTrack)
• Software:
  • 3D Slicer (latest stable version)
  • SlicerRoboTMS extension
  • Robot control interface

Setup Workflow

1. Imaging and Planning

1. Acquire high-resolution T1-weighted MRI
2. Import into 3D Slicer
3. Perform brain segmentation and surface reconstruction
4. Identify stimulation targets using atlases or fMRI
5. Plan coil trajectory and orientation

2. Registration and Calibration

1. Register patient space to image space
2. Calibrate robot coordinate system
3. Verify tracking system alignment
4. Test coil positioning accuracy

3. Intervention Execution

1. Load stimulation protocol
2. Execute robot-assisted positioning
3. Verify coil-target relationship
4. Deliver stimulation with real-time monitoring
5. Log position data for reproducibility

Key Features

Precision Control

• Position accuracy: < 1mm positioning error
• Orientation control: Tilt, rotation, and yaw adjustment
• Force compliance: Safe contact with scalp
• Emergency stops: Multiple safety interlocks

Data Integration

• Neuronavigation: Real-time coil-brain distance monitoring
• Stimulation logging: Automated session recording
• Outcome tracking: Integration with EMG/fMRI data
• Reproducibility: Exact session replication capability

Safety Considerations

Hardware Safety

• Collision detection: Automatic stop on unexpected contact
• Force limits: Maximum contact force thresholds
• Workspace boundaries: Software-defined safety zones
• Manual override: Immediate human operator control

Clinical Safety

• Motor threshold: Individualized intensity calibration
• Seizure risk: Contraindication screening
• Concurrent medications: Drug interaction awareness
• Adverse event monitoring: Standardized reporting

Advantages Over Manual TMS

Aspect	Manual TMS	Robo-TMS
Positioning accuracy	Operator-dependent (~5-10mm)	Sub-millimeter
Session reproducibility	Low	High
Multi-session targeting	Variable	Consistent
Operator fatigue	Significant	None
Integration with imaging	Limited	Seamless
Complex trajectories	Difficult	Automated

Limitations

1. Setup time: Initial calibration requires additional time
2. Cost: Robotic hardware investment
3. Training: Operators need robotics training
4. Emergency protocols: Requires defined failure modes
5. Movement compensation: Patient motion during stimulation

Related Skills

• brain-stimulation-dynamics-state: Brain stimulation network effects
• tms-eeg-biomarkers: TMS-EEG biomarker assessment
• neural-digital-twins-bci: Neural modeling for BCI
• neurocybernetic-large-scale-neuroscience: Neurocybernetic modeling

References

• SlicerRoboTMS: An Open-Source 3D Slicer Extension for Robot-Assisted Transcranial Magnetic Stimulation. arXiv:2604.25661v1
• 3D Slicer: https://www.slicer.org/