ArticleScientific data2023
Contact Endoscopy - Narrow Band Imaging (CE-NBI) data set for laryngeal lesion assessment.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- A Systematic Review of the Clinical Impact of Implementing Artificial Intelligence in Upper Aerodigestive Tract Endoscopy.Head & neck · 2025Pooled it
- Artificial Intelligence in Laryngeal Cancer Detection: A Systematic Review and Meta-Analysis.Current oncology (Toronto, Ont.) · 2025Pooled it
- Real-Time AI-Based Assessment of Glottic Lesions During Flexible Laryngoscopy: Comparison with Expert Evaluation and Histopathology.Medical sciences (Basel, Switzerland) · 2026Article
- The Burden and Risk Factors of Head and Neck Cancers in G20 Countries, 1990-2023.International dental journal · 2026Article
- Uncertainty-Aware Prediction Across Endoscopic Domains: Laryngeal Narrow-Band and Gastrointestinal Imaging.Biomedicines · 2026Article
- Multimodal deep learning for laryngeal squamous cell carcinoma staging using CT and laryngoscopy.European radiology · 2026Article
- Prediction of loss of heterozygosity in oral cavity dysplasia through vascular pattern.Frontiers in oral health · 2026Article
- Perpendicular Vascular Changes in NBI-CE of Laryngeal Lesions: Diagnostic Accuracy, Reproducibility, and Common Pitfalls.Diagnostics (Basel, Switzerland) · 2025Article
- Spine endoscopic atlas: an open-source dataset for surgical instrument segmentation.Scientific data · 2025Article
- Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.Nature communications · 2025Article
- Microvascularization of the Vocal Folds: Molecular Architecture, Functional Insights, and Personalized Research Perspectives.Journal of personalized medicine · 2025Review
- Investigating the key principles in two-step heterogeneous transfer learning for early laryngeal cancer identification.Scientific reports · 2025Article
- Global, regional, and national burden of laryngeal cancer in middle-aged and older adults from 1990 to 2021: an analysis of age and sex differences and attributable risk factors.Frontiers in public health · 2025Article
- Contact Endoscopy - Narrow Band Imaging (CE-NBI) data set for laryngeal lesion assessment.Scientific data · 2023Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The endoscopic examination of subepithelial vascular patterns within the vocal fold is crucial for clinicians seeking to distinguish between benign lesions and laryngeal cancer. Among innovative techniques, Contact Endoscopy combined with Narrow Band Imaging (CE-NBI) offers real-time visualization of these vascular structures. Despite the advent of CE-NBI, concerns have arisen regarding the subjective interpretation of its images. As a result, several computer-based solutions have been developed to address this issue. This study introduces the CE-NBI data set, the first publicly accessible data set that features enhanced and magnified visualizations of subepithelial blood vessels within the vocal fold. This data set encompasses 11144 images from 210 adult patients with pathological vocal fold conditions, where CE-NBI images are annotated using three distinct label categories. The data set has proven invaluable for numerous clinical assessments geared toward diagnosing laryngeal cancer using Optical Biopsy. Furthermore, given its versatility for various image analysis tasks, we have devised and implemented diverse image classification scenarios using Machine Learning (ML) approaches to address critical clinical challenges in assessing laryngeal lesions.
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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.