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Related Experiment Video

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Towards user-centered interactive medical image segmentation in VR with an assistive AI agent.

Pascal Spiegler1, Arash Harirpoush1, Yiming Xiao1

  • 1Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec Canada.

Virtual Reality
|January 9, 2026
PubMed
Summary

This study introduces SAMIRA, a conversational AI agent in virtual reality (VR) for medical image segmentation. SAMIRA enhances understanding and refines 3D medical visualizations through intuitive speech and interaction, improving radiological workflows.

Keywords:
AI agentAttention switchingClinical decision supportEye trackingFoundation modelHuman-in-the-loopMedical image segmentationMedical visualizationVirtual reality

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Virtual Reality

Background:

  • Manual segmentation of volumetric medical scans is time-consuming and error-prone.
  • Fully automatic segmentation algorithms can be improved with user feedback.
  • Integrating AI and VR offers a novel approach to medical image analysis.

Purpose of the Study:

  • To develop SAMIRA, a conversational AI agent for medical VR to assist in localizing, segmenting, and visualizing 3D medical concepts.
  • To evaluate the usability and effectiveness of SAMIRA in a human-in-the-loop segmentation workflow.
  • To compare different interaction modes (controller, head, eye tracking) for refining segmentation masks in VR.

Main Methods:

  • Development of SAMIRA, a conversational AI agent leveraging radiological AI foundation models and VR.
  • Implementation of speech-based interaction for understanding radiological features and generating segmentation masks.
  • Comparison of VR controller pointing, head pointing, and eye tracking for interactive segmentation refinement.
  • User study to evaluate system usability, task load, and training potential.

Main Results:

  • SAMIRA demonstrated high usability with a System Usability Scale (SUS) score of 90.0 ± 9.0.
  • The system achieved low overall task load for users.
  • Evaluations showed strong support for SAMIRA's guidance, training potential, and AI integration in radiological segmentation.

Conclusions:

  • SAMIRA offers an effective and intuitive AI-powered VR solution for medical image segmentation and visualization.
  • The conversational agent enhances understanding of radiological features and patient-specific anatomy.
  • The proposed human-in-the-loop VR system shows significant promise for improving radiological segmentation tasks.