SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers
Nikita Bedi1
, Anita Rau2, Alberto Paderno3, Hlu Vang1, Yoon Kyoung So1, F.~Christopher Holsinger1
1: Division of Head & Neck Surgery, Department of Otolaryngology, Stanford University, 2: Department of Biomedical Data Science, Stanford University, 3: Department of Otolaryngology–Head and Neck Surgery, Humanitas Research Hospital
Publication date: 2025/12/31
https://doi.org/10.59275/j.melba.2025-51gc
Abstract
Oropharyngeal cancer (OPC) is one of the few cancers with a rising incidence, driven primarily by increasing rates of human papillomavirus (HPV)-associated disease. Early detection and accurate delineation of OPC are critical for diagnosis, treatment planning and improving outcomes but remain challenging due to anatomical complexity and variability in clinical expertise. We present the SCOPE-HN dataset, a curated collection of annotated endoscopic images from 106 patients with histologically confirmed OPC, collected at Stanford between 2015 and 2023. The dataset consists of 942 RGB images extracted from diagnostic nasopharyngolaryngoscopy videos, with pixel-level annotations performed by expert Head and Neck surgeons. Annotations include 12 semantic classes representing tumor, normal anatomical structures, and common endoscopic artifacts. The SCOPE-HN dataset is publicly available at scope-hn.stanford.edu or bit.ly/SCOPE-HN under the Stanford University Dataset Research Use Agreement license.
Keywords
Oropharyngeal cancer · endoscopy · segmentation · dataset · annotation · machine learning · UADT
Bibtex
@article{melba:2025:047:bedi,
title = "SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers",
author = "Bedi, Nikita and Rau, Anita and Paderno, Alberto and Vang, Hlu and So, Yoon Kyoung and Holsinger, F.\textasciitilde Christopher",
journal = "Machine Learning for Biomedical Imaging",
volume = "3",
issue = "Special Issue on Open Data at MICCAI 2024–2025",
year = "2025",
pages = "913--918",
issn = "2766-905X",
doi = "https://doi.org/10.59275/j.melba.2025-51gc",
url = "https://melba-journal.org/2025:047"
}
RIS
TY - JOUR
AU - Bedi, Nikita
AU - Rau, Anita
AU - Paderno, Alberto
AU - Vang, Hlu
AU - So, Yoon Kyoung
AU - Holsinger, F.~Christopher
PY - 2025
TI - SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers
T2 - Machine Learning for Biomedical Imaging
VL - 3
IS - Special Issue on Open Data at MICCAI 2024–2025
SP - 913
EP - 918
SN - 2766-905X
DO - https://doi.org/10.59275/j.melba.2025-51gc
UR - https://melba-journal.org/2025:047
ER -