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Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing.

Shervin Dehghani1,2, Michael Sommersperger1, Peiyao Zhang2

  • 1Department of Computer Science, Technische Universität München, München 85748 Germany.

IEEE International Conference on Robotics and Automation : ICRA : [Proceedings]. IEEE International Conference on Robotics and Automation
|December 21, 2023
PubMed
Summary
This summary is machine-generated.

This study presents a framework for autonomous robotic navigation in retinal surgery using real-time processing of intraoperative Optical Coherent Tomography (iOCT) data. The system enables precise subretinal injections, improving surgical outcomes.

Keywords:
Computer Vision for Medical RoboticsMedical Robots and SystemsVision-Based Navigation

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Area of Science:

  • Ophthalmology
  • Robotics
  • Medical Imaging

Background:

  • Robotic platforms are increasingly used in delicate retinal surgeries.
  • Microscope-integrated intraoperative Optical Coherent Tomography (iOCT) provides high-resolution 3D imaging for surgical area understanding.
  • Combining robotics with iOCT enables task autonomy but presents challenges in data processing and system registration.

Purpose of the Study:

  • To propose a framework for autonomous robotic navigation for subretinal injection.
  • To address challenges in merging robotic systems with iOCT for enhanced surgical precision.
  • To enable intelligent real-time processing of iOCT volumes for autonomous surgical tasks.

Main Methods:

  • Developed a framework for autonomous robotic navigation using intelligent real-time processing of iOCT volumes.
  • Implemented an instrument pose estimation method and online registration between robotic and iOCT systems.
  • Introduced 'intelligent virtual B-scans' utilizing Convolutional Neural Networks (CNNs) for rapid instrument pose estimation.

Main Results:

  • Demonstrated precise and repeatable autonomous robotic navigation for subretinal injection.
  • Validated the framework's effectiveness on ex-vivo porcine eyes.
  • Successfully integrated real-time iOCT data processing for robotic surgical guidance.

Conclusions:

  • The proposed framework facilitates autonomous robotic navigation for subretinal injection.
  • Intelligent real-time iOCT processing and CNN-based pose estimation are crucial for surgical autonomy.
  • Further development is needed to address identified challenges and advance robotic retinal surgery systems.