arXiv cs.AI· Alda Jo\~ao Andrade, M\'onica Martins, Andr\'e Ferreira, Tarc\'isio Ara\'ujo, Lu\'is Lopes, Victor Alves·· 10 小时前AI 评分26
面向 ERCP 的精选内镜逆行胰胆管造影图像数据集发布
Curated endoscopic retrograde cholangiopancreatography images dataset
AI 导读
研究团队发布了一个精选 ERCP 图像数据集，包含来自 1.602 名患者的 19.018 张原始图像和 19.317 张处理后图像，其中 5.519 张已完成标注。所有图像由两名拥有 5 年以上经验、年操作超 400 例的消化科医生人工检查标注，并由一名 20 年以上经验的医生复核。分类实验验证了该数据集的效用与有效性，旨在为 ERCP 自动分析及胆胰疾病诊断提供基准。
正文 · 原文
Abstract:Endoscopic Retrograde Cholangiopancreatography (ERCP) is a key procedure in the diagnosis and treatment of biliary and pancreatic diseases. Artificial intelligence has been pointed as one solution to automatize diagnosis. However, public ERCP datasets are scarce, which limits the use of such approach. Therefore, this study aims to help fill this gap by providing a large and curated dataset. The collection is composed of 19.018 raw images and 19.317 processed from 1.602 patients. 5.519 images are labeled, which provides a ready to use dataset. All images were manually inspected and annotated by two gastroenterologist with more than 5 years of experience and reviewed by another gastroenterologist with more than 20 years of experience, all with more than 400 ERCP procedures annually. The utility and validity of the dataset is proven by a classification experiment. This collection aims to provide or contribute for a benchmark in automatic ERCP analysis and diagnosis of biliary and pancreatic diseases.
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI) |
| ACM classes: | E.m; I.4; I.2 |
| Cite as: | arXiv:2601.16759 [cs.CV] |
| (or arXiv:2601.16759v2 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2601.16759 arXiv-issued DOI via DataCite |
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| Journal reference: | Sci Data 13, 1485 (2026) |
| Related DOI: | https://doi.org/10.1038/s41597-026-07679-1
DOI(s) linking to related resources |
Submission history
From: Mónica Martins Carina Costa [view email]
[v1]
Fri, 23 Jan 2026 14:05:42 UTC (1,286 KB)
[v2]
Mon, 9 Nov 2026 21:09:20 UTC (1,286 KB)
来源：arXiv cs.AI · arxiv.org