ArticleInternational journal of computer assisted radiology and surgery2019
EyeSAM: graph-based localization and mapping of retinal vasculature during intraocular microsurgery.
Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Technical advances in robotic retinal surgery: a systematic review and future research directions.Journal of robotic surgery · 2026Review
- FOVEA: Preoperative and intraoperative retinal fundus images with optic disc and retinal vessel annotations.Scientific data · 2025Article
- Robotic Assistance for Intraocular Microsurgery: Challenges and Perspectives.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2022Article
- Eye Explorer: A robotic endoscope holder for eye surgery.The international journal of medical robotics + computer assisted surgery : MRCAS · 2021Article
- Learned optical flow for intra-operative tracking of the retinal fundus.International journal of computer assisted radiology and surgery · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
purposeRobot-assisted intraocular microsurgery can improve performance by aiding the surgeon in operating on delicate micron-scale anatomical structures of the eye. In order to account for the eyeball motion that is typical in intraocular surgery, there is a need for fast and accurate algorithms that map the retinal vasculature and localize the retina with respect to the microscope.
methodsThis work extends our previous work by a graph-based SLAM formulation using a sparse incremental smoothing and mapping (iSAM) algorithm.
resultsThe resulting technique, "EyeSAM," performs SLAM for intraoperative vitreoretinal surgical use while avoiding spurious duplication of structures as with the previous simpler technique. The technique also yields reduction in average pixel error in the camera motion estimation.
conclusionsThis work provides techniques to improve intraoperative tracking of retinal vasculature by handling loop closures and achieving increased robustness to quick shaky motions and drift due to uncertainties in the motion estimation.
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Registered trials
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