ArticleOptics letters2024
Fully automated OCT-based tissue screening system.
Article in Optics letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Tartrazine-enhanced visible-light OCT for deep-tissue imaging.Biomedical optics express · 2026Article
- Advanced imaging strategies in cardiac organoids: bridging the gap between structural complexity and functional analysis.Cardiovascular diabetology · 2026Review
- SON-dependent nuclear speckle rehabilitation alleviates proteinopathies.Nature communications · 2025Article
- SON-dependent nuclear speckle rehabilitation alleviates proteinopathies.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
- Update of
Authors and funding
8 authors.
Funding
Abstract
This study introduces an innovative optical coherence tomography (OCT) imaging system dedicated to high-throughput screening applications using ex vivo tissue culture. Leveraging OCT's non-invasive, high-resolution capabilities, the system is equipped with a custom-designed motorized platform and tissue detection ability for automated, successive imaging across samples. Transformer-based deep-learning segmentation algorithms further ensure robust, consistent, and efficient readouts meeting the standards for screening assays. Validated using retinal explant cultures from a mouse model of retinal degeneration, the system provides robust, rapid, reliable, unbiased, and comprehensive readouts of tissue response to treatments. This fully automated OCT-based system marks a significant advancement in tissue screening, promising to transform drug discovery, as well as other relevant research fields.
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What Socratic 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 Socratic graph.