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Related Experiment Video

Updated: Jun 12, 2025

Subretinal Transplantation of Human Embryonic Stem Cell Derived-retinal Pigment Epithelial Cells into a Large-eyed Model of Geographic Atrophy
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Towards Autonomous Retinal Microsurgery Using RGB-D Images.

Ji Woong Kim1, Shuwen Wei2, Peiyao Zhang1

  • 1Mechanical Engineering Dept at the Johns Hopkins University, Baltimore, MD 21218 USA.

IEEE Robotics and Automation Letters
|September 23, 2024
PubMed
Summary
This summary is machine-generated.

This study presents an autonomous robotic system for subretinal injection (SI) in retinal surgery. The framework uses real-time OCT and microscope imaging with AI for precise, safe needle navigation, achieving 30 successful trials in pig eyes.

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

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Area of Science:

  • Ophthalmology
  • Robotics
  • Medical Imaging

Background:

  • Retinal surgery demands extreme precision due to fragile tissue.
  • Robotic assistance and advanced imaging like OCT enhance surgical capabilities.
  • Subretinal injection (SI) requires accurate needle placement for drug delivery.

Purpose of the Study:

  • To develop an autonomous framework for real-time needle navigation during subretinal injection (SI).
  • To integrate optical coherence tomography (OCT) and microscope imaging with AI for automated surgical guidance.
  • To enhance safety and performance in robotic-assisted retinal surgery.

Main Methods:

  • Developed a system for autonomous needle navigation based on surgeon-defined waypoints.
  • Integrated microscope and OCT imaging with Convolutional Neural Networks (CNNs) for segmentation.
  • Employed model predictive control for trajectory generation respecting kinematic constraints.

Main Results:

  • Successfully demonstrated 30 autonomous subretinal injection (SI) trials in pig eyes.
  • The system achieved real-time navigation to the target subretinal space.
  • Preliminary comparisons showed enhanced safety and performance over human-assisted robotic control.

Conclusions:

  • The developed framework enables autonomous needle navigation for subretinal injection (SI).
  • Integration of OCT, CNNs, and model predictive control offers a safe and effective approach.
  • This technology has the potential to significantly improve outcomes in retinal surgery.