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Updated: Apr 27, 2026

Technical Approach for Infrared Tracking for Soft Tissue Navigation with a Holographic Head-Mounted Display and Preclinical Validation
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Real-time marker-less needle tracking for CT-guided interventions using multiple RGB cameras.

Max Steiger1, Tonia Mielke2, Oleksii Bashkanov2

  • 1Research Campus STIMULATE, University of Magdeburg, Otto-Hahn-Straße 2, 39106, Magdeburg, Saxony-Anhalt, Germany. max.steiger@ovgu.de.

International Journal of Computer Assisted Radiology and Surgery
|April 25, 2026
PubMed
Summary
This summary is machine-generated.

A novel marker-less needle tracking system using RGB cameras and AI demonstrated high accuracy (<2.70 mm error) in CT-guided interventions. This system overcomes limitations of marker-based methods, showing robust performance even with needle deflection and unknown needle types.

Keywords:
Biopsy needleDeep learningMarker-less video trackingSurgical tool tracking

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Area of Science:

  • Medical Imaging
  • Computer Vision
  • Surgical Technology

Background:

  • Marker-based tracking systems in CT-guided interventions are prone to occlusion and failure during needle deflection.
  • A marker-less system offers potential for improved reliability and streamlined integration in interventional procedures.

Purpose of the Study:

  • To develop and evaluate a proof-of-concept marker-less needle tracking system for CT-guided interventions.
  • To assess the system's accuracy, reliability, and robustness compared to existing marker-based systems.

Main Methods:

  • A U-Net-ConvNeXt architecture was employed with standard RGB cameras for needle detection and tracking.
  • A dataset of 35,000 annotated frames was created, encompassing diverse needle types and scenarios.
  • Tracking accuracy was evaluated against IR-based and image-based marker systems under static, dynamic, and deflection conditions.

Main Results:

  • The marker-less system achieved a 3D tracking error of 2.70 ± 1.07 mm with 3 cameras, outperforming marker-based systems (5.29 ± 1.85 mm).
  • Consistent accuracy was observed for unknown needle types, indicating strong generalization capabilities.
  • The system demonstrated a 99.4% needle-tip detection rate and robust performance during needle deflection, where marker-based systems failed.

Conclusions:

  • The proof-of-concept validates the feasibility of marker-less needle tracking for clinical applications.
  • The developed system shows potential for clinically relevant accuracy, reliability, and reduced complexity.
  • This marker-less approach offers a promising direction for advancing CT-guided interventions.