Computer-assisted systems are becoming broadly used in medicine. In endoscopy, most research focuses on the automatic detection of polyps or other pathologies, but localization and navigation of the endoscope are completely performed manually by physicians. To broaden this research and bring spatial Artificial Intelligence to endoscopies, data from complete procedures is needed. This paper introduces the Endomapper dataset, the first collection of complete endoscopy sequences acquired during regular medical practice, making secondary use of medical data. Its main purpose is to facilitate the development and evaluation of Visual Simultaneous Localization and Mapping (VSLAM) methods in real endoscopy data. The dataset contains more than 24 hours of video. It is the first endoscopic dataset that includes endoscope calibration as well as the original calibration videos. Meta-data and annotations associated with the dataset vary from the anatomical landmarks, procedure labeling, segmentations, reconstructions, simulated sequences with ground truth and same patient procedures. The software used in this paper is publicly available.

翻译：计算机辅助系统正逐渐广泛应用于医学领域。在内窥镜检查中，多数研究聚焦于息肉或其他病变的自动检测，但内窥镜的定位与导航完全由医生手动完成。为拓展该研究方向并将空间人工智能引入内窥镜领域，需要获取完整手术过程的数据。本文介绍了Endomapper数据集——首个在常规医疗实践中采集的完整内窥镜序列集合，实现了医疗数据的二次利用。其主要目的是促进真实内窥镜数据中视觉同步定位与建图（VSLAM）方法的开发与评估。该数据集包含超过24小时的视频，是首个包含内窥镜标定数据及原始标定视频的内窥镜数据集。其关联的元数据和标注信息涵盖解剖标志、手术标签、图像分割、三维重建、含真值的模拟序列以及同一患者的多次手术数据。本文所使用的软件已公开提供。