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Updated: Feb 8, 2026

Model Surgical Training: Skills Acquisition in Fetoscopic Laser Photocoagulation of Monochorionic Diamniotic Twin Placenta Using Realistic Simulators
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Towards computer-assisted TTTS: Laser ablation detection for workflow segmentation from fetoscopic video.

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Summary

This study introduces a deep learning framework for detecting laser ablation during fetal surgery for twin-to-twin transfusion syndrome (TTTS). The method shows promise for improving computer-assisted fetal therapies.

Keywords:
Deep learningEndoscopyTwin-to-twin transfusion syndrome (TTTS)Workflow segmentation

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Area of Science:

  • Medical technology
  • Computer vision
  • Surgical robotics

Background:

  • Intrauterine fetal surgery is crucial for congenital malformations.
  • Twin-to-twin transfusion syndrome (TTTS) requires ablating placental vessels via laser fiber.
  • Computer-assisted technologies can enhance surgical precision and safety in fetal interventions.

Purpose of the Study:

  • To develop a framework for automated detection of laser ablation during TTTS surgery.
  • To leverage computer vision and deep learning for real-time surgical feedback.
  • To support surgeons by identifying key procedural steps in intrauterine interventions.

Main Methods:

  • A deep learning approach using the ResNet101 architecture was employed.
  • The framework classifies surgical actions during laser ablation therapy.
  • Video data from five TTTS ablation procedures was analyzed.

Main Results:

  • A two-fold cross-validation was performed on approximately 50,000 frames.
  • Deep learning methods demonstrated effectiveness in detecting the ablation process.
  • The results indicate the potential of AI in enhancing fetal surgical procedures.

Conclusions:

  • This work represents the first automated photocoagulation detection using video in fetal surgery.
  • The developed technique can be integrated into assistive frameworks for advanced fetal therapies.
  • Future work will focus on semantic segmentation and localization of the ablation site.