Evidence map›Paper›PMID 37396671›Full record

ArticleProceedings. IEEE International Conference on Bioinformatics and Biomedicine2022

OCT-guided Robotic Subretinal Needle Injections: A Deep Learning-Based Registration Approach.

Kristina Mach, Shuwen Wei, Ji Woong Kim, Alejandro Martin-Gomez, Peiyao Zhang, Jin U Kang, M Ali Nasseri, Peter Gehlbach, Nassir Navab, Iulian Iordachita

Open access · greenAbstract read
In one paragraph

Article in Proceedings. IEEE International Conference on Bioinformatics and Biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.3field-weighted citation impact, top 4% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Deep Learning-Enhanced Robotic Subretinal Injection with Real-Time Retinal Motion Compensation.IEEE International Conference on Automation Science and Engineering (CASE) : [proceedings]. IEEE Conference on Automation Science and Engineering · 2025
    Article
  6. Towards Motion Compensation in Autonomous Robotic Subretinal Injections.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2025
    Article
  7. Article
  8. Review
  9. Autonomous Needle Navigation in Subretinal Injections via iOCT.IEEE robotics and automation letters · 2024
    Article
  10. Towards Autonomous Retinal Microsurgery Using RGB-D Images.IEEE robotics and automation letters · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Kristina MachLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Shuwen WeiLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Ji Woong KimLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Alejandro Martin-GomezLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Peiyao ZhangLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Jin U KangLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
M Ali NasseriAugenklinik und Poliklinik, Klinikum rechts der Isar der Technische Universität, Munich, Germany.
Peter GehlbachWilmer Eye Institute, Johns Hopkins Hospital, Baltimore, USA.
Nassir NavabLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Iulian IordachitaLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, USA.
Johns Hopkins University · USJohns Hopkins Hospital · USKlinikum rechts der Isar · DETechnical University of Munich · DE

Funding

Enabling Technology for Safe Robot-assisted Surgical MicromanipulationR01EB023943 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI GEHLBACH, PETER LOUIS, IORDACHITA, IULIAN IOAN · 2017 to 2024
$2.3M
Enabling technology for image-guided robot-assisted sub-retinal injectionsR01EB025883 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI IORDACHITA, IULIAN IOAN · 2019 to 2021
$1.5M
NIBIB NIH HHS R01 EB023943NIBIB NIH HHS R01 EB025883
6 · The paper itself

Abstract

Subretinal injection (SI) is an ophthalmic surgical procedure that allows for the direct injection of therapeutic substances into the subretinal space to treat vitreoretinal disorders. Although this treatment has grown in popularity, various factors contribute to its difficulty. These include the retina's fragile, nonregenerative tissue, as well as hand tremor and poor visual depth perception. In this context, the usage of robotic devices may reduce hand tremors and facilitate gradual and controlled SI. For the robot to successfully move to the target area, it needs to understand the spatial relationship between the attached needle and the tissue. The development of optical coherence tomography (OCT) imaging has resulted in a substantial advancement in visualizing retinal structures at micron resolution. This paper introduces a novel foundation for an OCT-guided robotic steering framework that enables a surgeon to plan and select targets within the OCT volume. At the same time, the robot automatically executes the trajectories necessary to achieve the selected targets. Our contribution consists of a novel combination of existing methods, creating an intraoperative OCT-Robot registration pipeline. We combined straightforward affine transformation computations with robot kinematics and a deep neural network-determined tool-tip location in OCT. We evaluate our framework's capability in a cadaveric pig eye open-sky procedure and using an aluminum target board. Targeting the subretinal space of the pig eye produced encouraging results with a mean Euclidean error of 23.8

Identifiers

PMID37396671
PMCPMC10312384
OpenAlexW4313452849

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.