ArticleJournal of biomedical optics2021
CNN-based CP-OCT sensor integrated with a subretinal injector for retinal boundary tracking and injection guidance.
Article in Journal of biomedical optics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 22 citations in OpenAlex.
- Simultaneous OCT A-scan depth ranging and C-scan volume imaging for intraoperative robotic retinal surgery guidance.Biomedical optics express · 2025Article
- Head-mounted surgical robots are an enabling technology for subretinal injections.Science robotics · 2025Article
- Robotics and optical coherence tomography: current works and future perspectives [Invited].Biomedical optics express · 2025Review
- High-resolutionBiomedical optics express · 2024Article
- Automatic and real-time tissue sensing for autonomous intestinal anastomosis using hybrid MLP-DC-CNN classifier-based optical coherence tomography.Biomedical optics express · 2024Article
- Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.Optics express · 2022Article
- Higher-order regression three-dimensional motion-compensation method for real-time optical coherence tomography volumetric imaging of the cornea.Journal of biomedical optics · 2022Article
- Development and ex-vivo validation of 36G polyimide cannulas integrating a guiding miniaturized OCT probe for robotic assisted subretinal injections.Biomedical optics express · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
significanceSubretinal injection is an effective way of delivering transplant genes and cells to treat many degenerative retinal diseases. However, the technique requires high-dexterity and microscale precision of experienced surgeons, who have to overcome the physiological hand tremor and limited visualization of the subretinal space.
aimTo automatically guide the axial motion of microsurgical tools (i.e., a subretinal injector) with microscale precision in real time using a fiber-optic common-path swept-source optical coherence tomography distal sensor. APPROACH: We propose, implement, and study real-time retinal boundary tracking of A-scan optical coherence tomography (OCT) images using a convolutional neural network (CNN) for automatic depth targeting of a selected retinal boundary for accurate subretinal injection guidance. A simplified 1D U-net is used for the retinal layer segmentation on A-scan OCT images. A Kalman filter, combining retinal boundary position measurement by CNN and velocity measurement by cross correlation between consecutive A-scan images, is applied to optimally estimate the retinal boundary position. Unwanted axial motions of the surgical tools are compensated by a piezoelectric linear motor based on the retinal boundary tracking.
resultsCNN-based segmentation on A-scan OCT images achieves the mean unsigned error (MUE) of ∼3 pixels (8.1 μm) using an ex vivo bovine retina model. GPU parallel computing allows real-time inference (∼2 ms) and thus real-time retinal boundary tracking. Involuntary tremors, which include low-frequency draft in hundreds of micrometers and physiological tremors in tens of micrometers, are compensated effectively. The standard deviations of photoreceptor (PR) and choroid (CH) boundary positions get as low as 10.8 μm when the depth targeting is activated.
conclusionsA CNN-based common-path OCT distal sensor successfully tracks retinal boundaries, especially the PR/CH boundary for subretinal injection, and automatically guides the tooltip's axial position in real time. The microscale depth targeting accuracy of our system shows its promising possibility for clinical application.
Indexed as
Identifiers
What 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.