126502 20230706095712.0 doi 10.1109/IROS47612.2022.9981742 sideral 132467 ART-2022-132467 eng Martínez Batlle, V. Universidad de Zaragoza (orcid)0000-0002-6837-934X Photometric single-view dense 3D reconstruction in endoscopy 2022 Visual SLAM inside the human body will open the way to computer-assisted navigation in endoscopy. However, due to space limitations, medical endoscopes only provide monocular images, leading to systems lacking true scale. In this paper, we exploit the controlled lighting in colonoscopy to achieve the first in-vivo 3D reconstruction of the human colon using photometric stereo on a calibrated monocular endoscope. Our method works in a real medical environment, providing both a suitable in-place calibration procedure and a depth estimation technique adapted to the colon's tubular geometry. We validate our method on simulated colonoscopies, obtaining a mean error of 7% on depth estimation, which is below 3 mm on average. Our qualitative results on the EndoMapper dataset show that the method is able to correctly estimate the colon shape in real human colonoscopies, paving the ground for truescale monocular SLAM in endoscopy. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/DGA/T45-17R 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-AEI-FEDER/PGC2018-096367-B-I00 info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 0.853 2022 Computer Science Applications 2022 Software 2022 Control and Systems Engineering 2022 Computer Vision and Pattern Recognition 2022 info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/acceptedVersion Martínez Montiel, J. M. Universidad de Zaragoza (orcid)0000-0002-3627-7306 Tardos, J. D. Universidad de Zaragoza (orcid)0000-0002-4518-5876 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 2022 (2022), 4904-4910 Proc. IEEE/RSJ Int. Conf. Intell. Rob. Syst. Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems 2153-0858 2520496 http://zaguan.unizar.es/record/126502/files/texto_completo.pdf Postprint 2909528 http://zaguan.unizar.es/record/126502/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:126502 articulos driver 2023-07-06-07:58:16 ARTICLE