SLAM (Simultaneous Localisation And Mapping) is one

methods provide real-time estimation of 3D models from the sole input of a hand-held camera, routinely in mobile robotics scenarios. Medical endoscopic sequences mimic a robotic scenario in which a hand-held camera (monocular endoscope) moves along an unknown trajectory while observing an unknown cavity. However, the feasibility and accuracy of SLAM methods have not been extensively validated with human in-vivo image sequences. In this work, we propose a monocular visual SLAM algorithm tailored to deal with medical image sequences in order to provide an up-to-scale 3D map of the observed cavity and the endoscope trajectory at frame rate. The algorithm is validated over synthetic data and human in-vivo sequences corresponding to fifteen la-paroscopic hernioplasties where accurate ground-truth distances are available. It can be concluded that the proposed procedure is: 1) non invasive, because only a standard monocular endoscope and a surgical tool are used; 2) convenient, because only a hand-controlled exploratory motion is needed; 3) fast, because the algorithm provides the 3D map and the trajectory in real time; 4) accurate, because it has been validated with respect to ground-truth; and 5) robust to inter-patient variability, because it has performed successfully over the validation sequences