A Reproducible COCO-Polygon Quality-Control Pipeline Improves Segmentation Stability in Endoscopic Airway Imaging

: Annotation-level QC enhances segmentation robustness without modifying the network architecture. The proposed workflow improves the reproducibility of results in endoscopic image segmentation and may support more stable geometry-based airway analysis in deep learning applications.

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Publication Details

Journal
Diagnostics
Published
2026-04-14
DOI
https://doi.org/10.3390/diagnostics16081160
Primary Topic
Advanced Radiotherapy Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

A Reproducible COCO-Polygon Quality-Control Pipeline Improves Segmentation Stability in Endoscopic Airway Imaging

Necati Olgun, Medine Atmaca, Ilkay Sibel Kervancı
Diagnostics
Advanced Radiotherapy Techniques
article

A Reproducible COCO-Polygon Quality-Control Pipeline Improves Segmentation Stability in Endoscopic Airway Imaging

Necati Olgun, Medine Atmaca, Ilkay Sibel Kervancı
article en

Abstract

: Annotation-level QC enhances segmentation robustness without modifying the network architecture. The proposed workflow improves the reproducibility of results in endoscopic image segmentation and may support more stable geometry-based airway analysis in deep learning applications.

DiagnosticsVol. 16(8)
Gaziantep University (TR)
Industry, innovation and infrastructure
Openalex Percentile: Top 21%
Advanced Radiotherapy Techniques
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A Reproducible COCO-Polygon Quality-Control Pipeline Improves Segmentation Stability in Endoscopic Airway Imaging — Necati Olgun, Medine Atmaca, et al. · Diagnostics (2026) | TGRS Research Map | TGRS