SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers

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 <a href='https://scope-hn.stanford.edu'>scope-hn.stanford.edu</a> or <a href='https://bit.ly/SCOPE-HN'>bit.ly/SCOPE-HN</a> under the Stanford University Dataset Research Use Agreement license.

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Publication Details

Journal
The Journal of Machine Learning for Biomedical Imaging
Published
2025-12-31
DOI
https://doi.org/10.59275/j.melba.2025-51gc
Primary Topic
Head and Neck Cancer Studies
Type
article
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article

SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers

Yoon Kyoung So, Alberto Paderno, Nikita Bedi, Anita Rau et al.
The Journal of Machine Learning for Biomedical Imaging
Head and Neck Cancer Studies
article

SCOPE-HN: A Segmentation-based Collection of OroPharyngeal Structures Using Flexible Endoscopy for Head and Neck Cancers

Yoon Kyoung So, Alberto Paderno, Nikita Bedi, Anita Rau, Hlu Vang, F.~Christopher Holsinger
article en

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 <a href='https://scope-hn.stanford.edu'>scope-hn.stanford.edu</a> or <a href='https://bit.ly/SCOPE-HN'>bit.ly/SCOPE-HN</a> under the Stanford University Dataset Research Use Agreement license.

The Journal of Machine Learning for Biomedical ImagingVol. 3(MICCAI Open Data 2024-2025)
Humanitas University (IT), IRCCS Humanitas Research Hospital (IT), Stanford University (US)
Good health and well-being
Openalex Percentile: Top 21%
Head and Neck Cancer Studies
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