ArticleProceedings of machine learning research2021
Towards Autonomous Eye Surgery by Combining Deep Imitation Learning with Optimal Control.
Article in Proceedings of machine learning research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in ophthalmology: a bibliometric analysis of the 5-year trends in literature.Frontiers in medicine · 2025Pooled it
- Artificial Intelligence in Ophthalmology: Current Status, Challenges, and Future Perspectives.Health care science · 2026Review
- Bibliometric analysis of deep learning for surgical instrument segmentation, detection and tracking in minimally invasive surgery.Frontiers in digital health · 2026Review
- A Deep Learning-Driven Autonomous System for Retinal Vein Cannulation: Validation Using a Chicken Embryo Model.Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems · 2025Article
- Will your next surgeon be a robot? Autonomy and AI in robotic surgery.Science robotics · 2025Review
- Autonomous Needle Navigation in Subretinal Injections via iOCT.IEEE robotics and automation letters · 2024Article
- Towards Autonomous Retinal Microsurgery Using RGB-D Images.IEEE robotics and automation letters · 2024Article
- Microsurgery Robots: Applications, Design, and Development.Sensors (Basel, Switzerland) · 2023Review
- Robotic Assistance for Intraocular Microsurgery: Challenges and Perspectives.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2022Article
- Spotlight-based 3D Instrument Guidance for Autonomous Task in Robot-assisted Retinal Surgery.IEEE robotics and automation letters · 2021Article
- Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery?Sensors (Basel, Switzerland) · 2021Review
- Autonomous Needle Navigation in Retinal Microsurgery: Evaluation inIEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and AutomationArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
During retinal microsurgery, precise manipulation of the delicate retinal tissue is required for positive surgical outcome. However, accurate manipulation and navigation of surgical tools remain difficult due to a constrained workspace and the top-down view during the surgery, which limits the surgeon's ability to estimate depth. To alleviate such difficulty, we propose to automate the tool-navigation task by learning to predict relative goal position on the retinal surface from the current tool-tip position. Given an estimated target on the retina, we generate an optimal trajectory leading to the predicted goal while imposing safety-related physical constraints aimed to minimize tissue damage. As an extended task, we generate goal predictions to various points across the retina to localize eye geometry and further generate safe trajectories within the estimated confines. Through experiments in both simulation and with several eye phantoms, we demonstrate that our framework can permit navigation to various points on the retina within 0.089mm and 0.118mm in xy error which is less than the human's surgeon mean tremor at the tool-tip of 0.180mm. All safety constraints were fulfilled and the algorithm was robust to previously unseen eyes as well as unseen objects in the scene. Live video demonstration is available here: https://youtu.be/n5j5jCCelXk.
Indexed as
Identifiers
34712957PMC8549631What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.