ArticleBiomedical optics express2017
Automatic and robust segmentation of endoscopic OCT images and optical staining.
Article in Biomedical optics express, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- The LMIT: Light-mediated minimally-invasive theranostics in oncology.Theranostics · 2024Review
- Wavelet attention network for the segmentation of layer structures on OCT images.Biomedical optics express · 2022Article
- Direct Visualization and Quantitative Imaging of Small Airway Anatomy In Vivo Using Deep Learning Assisted Diffractive OCT.IEEE transactions on bio-medical engineering · 2022Article
- Connectivity-based deep learning approach for segmentation of the epithelium inBiomedical optics express · 2021Article
- Tissue self-attention network for the segmentation of optical coherence tomography images on the esophagus.Biomedical optics express · 2021Article
- Colon phantoms with cancer lesions for endoscopic characterization with optical coherence tomography.Biomedical optics express · 2021Article
- Adversarial convolutional network for esophageal tissue segmentation on OCT images.Biomedical optics express · 2020Article
- Robust, accurate depth-resolved attenuation characterization in optical coherence tomography.Biomedical optics express · 2020Article
- Parallel deep neural networks for endoscopic OCT image segmentation.Biomedical optics express · 2019Article
- Fast esophageal layer segmentation in OCT images of guinea pigs based on sparse Bayesian classification and graph search.Biomedical optics express · 2019Article
- Automatic three-dimensional segmentation of endoscopic airway OCT images.Biomedical optics express · 2019Article
- Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue.Journal of medical imaging (Bellingham, Wash.) · 2019Article
- Robust layer segmentation of esophageal OCT images based on graph search using edge-enhanced weights.Biomedical optics express · 2018Article
- Automated 3D segmentation of methyl isocyanate-exposed rat trachea using an ultra-thin, fully fiber optic optical coherence endoscopic probe.Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
We report a generic method for automatic segmentation of endoscopic optical coherence tomography (OCT) images. In this method, OCT images are first processed with
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.