DefSLAM: Tracking and Mapping of Deforming Scenes from Monocular Sequences

Monocular simultaneous localization and mapping (SLAM) algorithms perform robustly when observing rigid scenes; however, they fail when the observed scene deforms, for example, in medical endoscopy applications. In this article, we present DefSLAM, the first monocular SLAM capable of operating in deforming scenes in real time. Our approach intertwines Shape-from-Template (SfT) and Non-Rigid Structure-from-Motion (NRSfM) techniques to deal with the exploratory sequences typical of SLAM. A deformation tracking thread recovers the pose of the camera and the deformation of the observed map, at frame rate, by means of SfT processing a template that models the scene shape-at-rest. A deformation mapping thread runs in parallel with the tracking to update the template, at keyframe rate, by means of an isometric NRSfM processing a batch of full perspective keyframes. In our experiments, DefSLAM processes close-up sequences of deforming scenes, both in a laboratory-controlled experiment and in medical endoscopy sequences, producing accurate 3-D models of the scene with respect to the moving camera

Mortality and Morbidity Following Endovascular Repair of Abdominal Aortic Aneurysms: Analysis of Two Single Centre Experiences

AbstractObjective to show how differences in anatomical and physiological risk factors can affect the outcome of endovascular repair of AAA by describing the experience of two centres with different selection policies. Methods one hundred and thirty-five patients (group I) were treated at Queen's Medical Centre (Nottingham, U.K.) using 101 in-house made and 34 manufactured stent-grafts. Median diameter, length and angulation of the proximal aneurysm neck were 26 mm, 27 mm, 40°, respectively. Seventy-six patients had ischaemic heart disease, 47 had left ventricular failure, median forced expiratory volume in one second (FEV1) was 83%, median creatinine was 100 μmol/l and median age was 72 years. Fifty patients (group II) were treated at Timone Hospital (Marseilles, France) using seven in-house made and 43 manufactured stent-grafts. Median diameter, length and angulation of the proximal aneurysm neck were 25 mm, 34 mm, 33°, respectively. Thirteen patients had ischaemic heart disease, two had left ventricular failure, median forced expiratory volume in one second was 101%, median creatinine was 108 μmol/l and mean age was 72 years. Results anatomical characteristics of the proximal neck were significantly worse in group I (p=0.02 for the three variables). Cardiac comorbidities were more frequent and mean FEV1 was lower in group I (p<0.0001 and p=0.001, respectively. Median aneurysm diameter was significantly greater in group I (65 mm) than in group II (53 mm) (p<0.001). Postoperative mortality was 9% and 0% in groups I and II respectively (p=0.03). The incidence of technical complications (groin wound complications and side branches endoleaks being excluded) was 20% and 0% in groups I and II, respectively (p=0.0006). Conclusion postoperative mortality and technical complication rates were significantly greater in group I than in group II, readily explained by poorer general condition and worse anatomical characteristics of the proximal neck in group I

An Analysis of Errors in Graph-Based Keypoint Matching and Proposed Solutions

International audienceAn error occurs in graph-based keypoint matching when key-points in two different images are matched by an algorithm but do not correspond to the same physical point. Most previous methods acquire keypoints in a black-box manner, and focus on developing better algorithms to match the provided points. However to study the complete performance of a matching system one has to study errors through the whole matching pipeline, from keypoint detection, candidate selection to graph optimisation. We show that in the full pipeline there are six different types of errors that cause mismatches. We then present a matching framework designed to reduce these errors. We achieve this by adapting keypoint detectors to better suit the needs of graph-based matching, and achieve better graph constraints by exploiting more information from their keypoints. Our framework is applicable in general images and can handle clutter and motion discontinuities. We also propose a method to identify many mismatches a posteriori based on Left-Right Consistency inspired by stereo matching due to the asymmetric way we detect keypoints and define the graph

The Moby Dick architecture

This document is deliverable II.3.1, and presents the the MobyDick architecture. The introduction outlines the main areas of use and the main characteristics of the Pocket Companion, and ends up with the overall demands we put on the architecture. In chapter 2 Quality of Service (QoS) as we use it in MobyDick QoS is presented. It gives the foundation the adaptability used in the chapters to follow. In chapter 3 an overview of the software architecture of the Pocket Companion is presented. The security architecture of the Pocket Companion is presented in chapter 4, and the consistency architecture is presented in chapter 5. In chapter 6, the system\ud architecture of the Pocket Companion is outlined