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.

翻译：内镜逆行胰胆管造影（ERCP）是诊断和治疗胆胰疾病的关键技术。人工智能已被视为实现诊断自动化的一种解决方案。然而，公开的ERCP数据集稀缺，限制了此类方法的应用。因此，本研究旨在通过提供一个大规模精选数据集来帮助填补这一空白。该数据集包含来自1,602名患者的19,018张原始图像与19,317张处理后图像，其中5,519张图像已标注，构成可直接使用的数据集。所有图像均由两名具有5年以上经验、每年操作超过400例ERCP的消化内科医师人工检查与标注，并由另一名具有20年以上经验、每年操作超过400例ERCP的消化内科医师审核。通过分类实验验证了数据集的实用性与有效性。本数据集旨在为胆胰疾病的自动ERCP分析与诊断提供或贡献基准标准。