128096 20241125101159.0 doi 10.1038/s41597-023-02564-7 sideral 135277 ART-2023-135277 eng Azagra, Pablo Universidad de Zaragoza (orcid)0000-0002-3567-3294 Endomapper dataset of complete calibrated endoscopy procedures 2023 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/DGA/T45-23R info:eu-repo/grantAgreement/EC/H2020/863146/EU/EndoMapper: Real-time mapping from endoscopic video/EndoMapper This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 863146-EndoMapper info:eu-repo/grantAgreement/ES/MCIU/FPU20-06782 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 5.8 2023 MULTIDISCIPLINARY SCIENCES 16 / 134 = 0.119 2023 Q1 T1 1.937 2023 Education 2023 Q1 Computer Science Applications 2023 Q1 Statistics, Probability and Uncertainty 2023 Q1 Library and Information Sciences 2023 Q1 Statistics and Probability 2023 Q1 Information Systems 2023 Q1 11.2 2023 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Sostres, Carlos Universidad de Zaragoza (orcid)0000-0001-7466-3876 Ferrández, Ángel Universidad de Zaragoza (orcid)0000-0003-2280-9372 Riazuelo, Luis Universidad de Zaragoza (orcid)0000-0002-6722-5541 Tomasini, Clara Universidad de Zaragoza (orcid)0009-0001-2112-0939 Barbed, O. León Universidad de Zaragoza (orcid)0000-0001-8191-6261 Morlana, Javier Universidad de Zaragoza Recasens, David Universidad de Zaragoza Batlle Martínez, Víctor Universidad de Zaragoza (orcid)0000-0002-6837-934X Gómez-Rodríguez, Juan J. Universidad de Zaragoza Elvira, Richard Universidad de Zaragoza López, Julia Oriol, Cristina Civera, Javier Universidad de Zaragoza (orcid)0000-0003-1368-1151 Tardós, Juan D. Universidad de Zaragoza (orcid)0000-0002-4518-5876 Murillo, Ana C. Universidad de Zaragoza (orcid)0000-0002-7580-9037 Lanas, Angel Universidad de Zaragoza (orcid)0000-0001-5932-2889 Montiel, José M. M. Universidad de Zaragoza (orcid)0000-0002-3627-7306 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 1007 610 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Medicina 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 10, 1 (2023), 671 [16 pp.] Sci. data SCIENTIFIC DATA 2052-4463 4836350 http://zaguan.unizar.es/record/128096/files/texto_completo.pdf Versión publicada 2671691 http://zaguan.unizar.es/record/128096/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:128096 articulos driver 2024-11-22-12:10:58 ARTICLE