ArticleJournal of clinical medicine2025
Automatic Segmentation of the Nasolacrimal Canal: Application of the nnU-Net v2 Model in CBCT Imaging.
Article in Journal of clinical medicine, 2025. 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.
- Deep learning based hybrid system for automatic detection and classification of nasopalatine canal in cone beam computed tomography images.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Deep Learning-Based Automated Segmentation and Multi-Parametric Quantitative Assessment of the Lacrimal Drainage System on CT-DCG.Translational vision science & technology · 2026Article
- Deep learning-based automatic segmentation of MRONJ lesions on CBCT images.BMC oral health · 2026Article
- Accuracy of artificial intelligence applications in periodontics: a thematic narrative review.Frontiers in dental medicine · 2026Review
- Enhanced diagnostic pipeline for maxillary sinus-maxillary molars relationships: a novel implementation of Detectron2 with faster R-CNN R50 FPN 3x on CBCT images.BMC oral health · 2025Article
- Automatic Segmentation of the Infraorbital Canal in CBCT Images: Anatomical Structure Recognition Using Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2025Article
- Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility.BMC medical imaging · 2025Article
- Segmentation of the nasopalatine canal and detection of canal furcation status with artificial intelligence on cone-beam computed tomography images.Oral radiology · 2025Article
- AI in Medical Imaging and Image Processing.Journal of clinical medicine · 2025Article
- Enhancing perihematomal edema segmentation: integrating prior knowledge with deep learning for enhanced accuracy and interpretability.Quantitative imaging in medicine and surgery · 2025Article
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
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.