ArticleBiomedical optics express2022
Automatic and quantitative measurement of alveolar bone level in OCT images using deep learning.
Article in Biomedical optics express, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- The Application and Performance of Artificial Intelligence (AI) Models in the Diagnosis, Classification, and Prediction of Periodontal Diseases: A Systematic Review.Diagnostics (Basel, Switzerland) · 2025Review
- Optical Coherence Tomography for Assessing the Severity of Dental Caries: An In Vitro Validation Study.Dentistry journal · 2025Article
- Impact of Optical Coherence Tomography (OCT) for Periodontitis Diagnostics: Current Overview and Advances.Dentistry journal · 2025Review
- Segmentation of Pulp and Pulp Stones with Automatic Deep Learning in Panoramic Radiographs: An Artificial Intelligence Study.Dentistry journal · 2025Article
- Alveolar bone loss is associated with oral cancer: a case-control study.Frontiers in oral health · 2025Article
- Segmentation of periapical lesions with automatic deep learning on panoramic radiographs: an artificial intelligence study.BMC oral health · 2024Article
- Adaptive contour-tracking to aid wide-field swept-source optical coherence tomography imaging of large objects with uneven surface topology.Biomedical optics express · 2024Article
- High-speed, long-range and wide-field OCT for in vivo 3D imaging of the oral cavity achieved by a 600 kHz swept source laser.Biomedical optics express · 2024Article
- Automatic classification of 3D positional relationship between mandibular third molar and inferior alveolar canal using a distance-aware network.BMC oral health · 2023Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose a method to automatically segment the periodontal structures of the tooth enamel and the alveolar bone using convolutional neural network (CNN) and to measure quantitatively and automatically the alveolar bone level (ABL) by detecting the cemento-enamel junction and the alveolar bone crest in optical coherence tomography (OCT) images. The tooth enamel and the alveolar bone regions were automatically segmented using U-Net, Dense-UNet, and U
Identifiers
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.