Evidence map›Paper›PMID 41339627›Full record

ArticleScientific data2025

Upper Airway Anatomical Landmark Dataset for Automated Bronchoscopy and Intubation.

Ruoyi Hao, Yang Zhang, Zhiqing Tang, Yang Zhou, Lalithkumar Seenivasan, Catherine Po Ling Chan, Jason Ying Kuen Chan, Shuhui Xu, Neville Wei Yang Teo, Kaijun Tay and 7 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Ruoyi Hao *Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.ORCID 0009-0000-0341-6763
Yang Zhang *School of Mechanical Engineering, Hubei University of Technology, Wuhan, China.
Zhiqing TangDepartment of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.
Yang ZhouSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China.
Lalithkumar SeenivasanDepartment of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China.
Catherine Po Ling ChanDepartment of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong, Hong Kong SAR, China.
Jason Ying Kuen ChanDepartment of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0002-9480-4637
Shuhui XuDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Neville Wei Yang TeoDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Kaijun TayDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Vanessa Yee Jueen TanDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Jiun Fong ThongDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Kimberley Liqin KiongDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Shaun LohDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Song Tar TohDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Chwee Ming LimDepartment of Otorhinolaryngology-Head and Neck Surgery, Singapore General Hospital, Singapore, Singapore.
Hongliang RenDepartment of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China. hlren@ieee.org.

Funding

Research Grants Council, University Grants Committee (RGC, UGC) CRF-C4026-21G
6 · The paper itself

Abstract

Bronchoscopy and intubation play crucial roles in respiratory disease diagnosis and treatment, yet the automation of their initial insertion phase remains limited. Advanced image analysis presents a viable solution to this challenge. However, insufficient comprehensive, publicly available datasets for training such models have hindered progress. We present a novel Upper Airway Anatomical Landmark (UAAL) Dataset, which annotates multiple anatomical landmark classes visualized through a bronchoscope, including the nose, nostril, channel, glottis, glottic aperture, vocal fold, and trachea, encompassing the entire upper respiratory tract from the nasal cavity to the trachea. It includes 3,814 clinical images from 82 patients with 10,330 annotations (4,910 instance segmentation masks and 5,420 bounding boxes) across 8 classes and 2,746 supplementary phantom images with 4,526 annotations (2,795 instance segmentation masks and 1,551 bounding boxes) across 9 classes. With its key contributions of diverse anatomical coverage, clinical data, supplementary phantom data, and public accessibility, this dataset will contribute to bronchoscopy and intubation automation systems, facilitating their transition from laboratory to clinical applications.

Indexed as

Anatomic LandmarksBronchoscopyIntubation, IntratrachealRespiratory SystemAutomationDatasets as TopicHumansTrachea

Identifiers

PMID41339627
PMCPMC12675523

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.