Imparting 3D representations to artificial intelligence for a full assessment of pressure injuries.

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning methods. The main objective of this dissertation is to prove the efficiency of Deep Learning techniques in tackling one of the important health issues we are facing in our society, through medical imaging. Pressure injuries are a dermatology related health issue associated with increased morbidity and health care costs. Managing pressure injuries appropriately is increasingly important for all the professionals in wound care. Using 2D photographs and 3D meshes of these wounds, collected from collaborating hospitals, our mission is to create intelligent systems for a full non-intrusive assessment of these wounds. Five main tasks have been achieved in this study: a literature review of wound imaging methods using machine learning techniques, the classification and segmentation of the tissue types inside the pressure injury, the segmentation of these wounds and the design of an end-to-end system which measures all the necessary quantitative information from 3D meshes for an efficient assessment of PIs, and the integration of the assessment imaging techniques in a web-based application

Neural Radiance Fields: Past, Present, and Future

The various aspects like modeling and interpreting 3D environments and surroundings have enticed humans to progress their research in 3D Computer Vision, Computer Graphics, and Machine Learning. An attempt made by Mildenhall et al in their paper about NeRFs (Neural Radiance Fields) led to a boom in Computer Graphics, Robotics, Computer Vision, and the possible scope of High-Resolution Low Storage Augmented Reality and Virtual Reality-based 3D models have gained traction from res with more than 1000 preprints related to NeRFs published. This paper serves as a bridge for people starting to study these fields by building on the basics of Mathematics, Geometry, Computer Vision, and Computer Graphics to the difficulties encountered in Implicit Representations at the intersection of all these disciplines. This survey provides the history of rendering, Implicit Learning, and NeRFs, the progression of research on NeRFs, and the potential applications and implications of NeRFs in today's world. In doing so, this survey categorizes all the NeRF-related research in terms of the datasets used, objective functions, applications solved, and evaluation criteria for these applications.Comment: 413 pages, 9 figures, 277 citation

Large Scale 3D Mapping of Indoor Environments Using a Handheld RGBD Camera

The goal of this research is to investigate the problem of reconstructing a 3D representation of an environment, of arbitrary size, using a handheld color and depth (RGBD) sensor. The focus of this dissertation is to examine four of the underlying subproblems to this system: camera tracking, loop closure, data storage, and integration. First, a system for 3D reconstruction of large indoor planar environments with data captured from an RGBD sensor mounted on a mobile robotic platform is presented. An algorithm for constructing nearly drift-free 3D occupancy grids of large indoor environments in an online manner is also presented. This approach combines data from an odometry sensor with output from a visual registration algorithm, and it enforces a Manhattan world constraint by utilizing factor graphs to produce an accurate online estimate of the trajectory of the mobile robotic platform. Through several experiments in environments with varying sizes and construction it is shown that this method reduces rotational and translational drift significantly without performing any loop closing techniques. In addition the advantages and limitations of an octree data structure representation of a 3D environment is examined. Second, the problem of sensor tracking, specifically the use of the KinectFusion algorithm to align two subsequent point clouds generated by an RGBD sensor, is studied. A method to overcome a significant limitation of the Iterative Closest Point (ICP) algorithm used in KinectFusion is proposed, namely, its sole reliance upon geometric information. The proposed method uses both geometric and color information in a direct manner that uses all the data in order to accurately estimate camera pose. Data association is performed by computing a warp between the two color images associated with two RGBD point clouds using the Lucas-Kanade algorithm. A subsequent step then estimates the transformation between the point clouds using either a point-to-point or point-to-plane error metric. Scenarios in which each of these metrics fails are described, and a normal covariance test for automatically selecting between them is proposed. Together, Lucas-Kanade data association (LKDA) along with covariance testing enables robust camera tracking through areas of low geometrical features, while at the same time retaining accuracy in environments in which the existing ICP technique succeeds. Experimental results on several publicly available datasets demonstrate the improved performance both qualitatively and quantitatively. Third, the choice of state space in the context of performing loop closure is revisited. Although a relative state space has been discounted by previous authors, it is shown that such a state space is actually extremely powerful, able to achieve recognizable results after just one iteration. The power behind the technique is that changing the orientation of one node is able to affect other nodes. At the same time, the approach --- which is referred to as Pose Optimization using a Relative State Space (POReSS) --- is fast because, like the more popular incremental state space, the Jacobian never needs to be explicitly computed. Furthermore, it is shown that while POReSS is able to quickly compute a solution near the global optimum, it is not precise enough to perform the fine adjustments necessary to achieve acceptable results. As a result, a method to augment POReSS with a fast variant of Gauss-Seidel --- which is referred to as Graph-Seidel --- on a global state space to allow the solution to settle closer to the global minimum is proposed. Through a set of experiments, it is shown that this combination of POReSS and Graph-Seidel is not only faster but achieves a lower residual than other non-linear algebra techniques. Moreover, unlike the linear algebra-based techniques, it is shown that this approach scales to very large graphs. In addition to revisiting the idea of using a relative state space, the benefits of only optimizing the rotational components of a trajectory in order to perform loop closing is examined (rPOReSS). Finally, an incremental implementation of the rotational optimization is proposed (irPOReSS)

Large Model Visualization : Techniques and Applications

The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture.The size of datasets in scientific computing is rapidly increasing. This increase is caused by a boost of processing power in the past years, which in turn was invested in an increase of the accuracy and the size of the models. A similar trend enabled a significant improvement of medical scanners; more than 1000 slices of a resolution of 512x512 can be generated by modern scanners in daily practice. Even in computer-aided engineering typical models eas-ily contain several million polygons. Unfortunately, the data complexity is growing faster than the rendering performance of modern computer systems. This is not only due to the slower growing graphics performance of the graphics subsystems, but in particular because of the significantly slower growing memory bandwidth for the transfer of the geometry and image data from the main memory to the graphics accelerator. Large model visualization addresses this growing divide between data complexity and rendering performance. Most methods focus on the reduction of the geometric or pixel complexity, and hence also the memory bandwidth requirements are reduced. In this dissertation, we discuss new approaches from three different research areas. All approaches target at the reduction of the processing complexity to achieve an interactive visualization of large datasets. In the second part, we introduce applications of the presented ap-proaches. Specifically, we introduce the new VIVENDI system for the interactive virtual endoscopy and other applications from mechanical engineering, scientific computing, and architecture

3D Multimodal Interaction with Physically-based Virtual Environments

The virtual has become a huge field of exploration for researchers: it could assist the surgeon, help the prototyping of industrial objects, simulate natural phenomena, be a fantastic time machine or entertain users through games or movies. Far beyond the only visual rendering of the virtual environment, the Virtual Reality aims at -literally- immersing the user in the virtual world. VR technologies simulate digital environments with which users can interact and, as a result, perceive through different modalities the effects of their actions in real time. The challenges are huge: the user's motions need to be perceived and to have an immediate impact on the virtual world by modifying the objects in real-time. In addition, the targeted immersion of the user is not only visual: auditory or haptic feedback needs to be taken into account, merging all the sensory modalities of the user into a multimodal answer. The global objective of my research activities is to improve 3D interaction with complex virtual environments by proposing novel approaches for physically-based and multimodal interaction. I have laid the foundations of my work on designing the interactions with complex virtual worlds, referring to a higher demand in the characteristics of the virtual environments. My research could be described within three main research axes inherent to the 3D interaction loop: (1) the physically-based modeling of the virtual world to take into account the complexity of the virtual object behavior, their topology modifications as well as their interactions, (2) the multimodal feedback for combining the sensory modalities into a global answer from the virtual world to the user and (3) the design of body-based 3D interaction techniques and devices for establishing the interfaces between the user and the virtual world. All these contributions could be gathered in a general framework within the 3D interaction loop. By improving all the components of this framework, I aim at proposing approaches that could be used in future virtual reality applications but also more generally in other areas such as medical simulation, gesture training, robotics, virtual prototyping for the industry or web contents.Le virtuel est devenu un vaste champ d'exploration pour la recherche et offre de nos jours de nombreuses possibilités : assister le chirurgien, réaliser des prototypes de pièces industrielles, simuler des phénomènes naturels, remonter dans le temps ou proposer des applications ludiques aux utilisateurs au travers de jeux ou de films. Bien plus que le rendu purement visuel d'environnement virtuel, la réalité virtuelle aspire à -littéralement- immerger l'utilisateur dans le monde virtuel. L'utilisateur peut ainsi interagir avec le contenu numérique et percevoir les effets de ses actions au travers de différents retours sensoriels. Permettre une véritable immersion de l'utilisateur dans des environnements virtuels de plus en plus complexes confronte la recherche en réalité virtuelle à des défis importants: les gestes de l'utilisateur doivent être capturés puis directement transmis au monde virtuel afin de le modifier en temps-réel. Les retours sensoriels ne sont pas uniquement visuels mais doivent être combinés avec les retours auditifs ou haptiques dans une réponse globale multimodale. L'objectif principal de mes activités de recherche consiste à améliorer l'interaction 3D avec des environnements virtuels complexes en proposant de nouvelles approches utilisant la simulation physique et exploitant au mieux les différentes modalités sensorielles. Dans mes travaux, je m'intéresse tout particulièrement à concevoir des interactions avec des mondes virtuels complexes. Mon approche peut être décrite au travers de trois axes principaux de recherche: (1) la modélisation dans les mondes virtuels d'environnements physiques plausibles où les objets réagissent de manière naturelle, même lorsque leur topologie est modifiée ou lorsqu'ils sont en interaction avec d'autres objets, (2) la mise en place de retours sensoriels multimodaux vers l'utilisateur intégrant des composantes visuelles, haptiques et/ou sonores, (3) la prise en compte de l'interaction physique de l'utilisateur avec le monde virtuel dans toute sa richesse : mouvements de la tête, des deux mains, des doigts, des jambes, voire de tout le corps, en concevant de nouveaux dispositifs ou de nouvelles techniques d'interactions 3D. Les différentes contributions que j'ai proposées dans chacun de ces trois axes peuvent être regroupées au sein d'un cadre plus général englobant toute la boucle d'interaction 3D avec les environnements virtuels. Elles ouvrent des perspectives pour de futures applications en réalité virtuelle mais également plus généralement dans d'autres domaines tels que la simulation médicale, l'apprentissage de gestes, la robotique, le prototypage virtuel pour l'industrie ou bien les contenus web

3D Multimodal Interaction with Physically-based Virtual Environments

The virtual has become a huge field of exploration for researchers: it could assist the surgeon, help the prototyping of industrial objects, simulate natural phenomena, be a fantastic time machine or entertain users through games or movies. Far beyond the only visual rendering of the virtual environment, the Virtual Reality aims at -literally- immersing the user in the virtual world. VR technologies simulate digital environments with which users can interact and, as a result, perceive through different modalities the effects of their actions in real time. The challenges are huge: the user's motions need to be perceived and to have an immediate impact on the virtual world by modifying the objects in real-time. In addition, the targeted immersion of the user is not only visual: auditory or haptic feedback needs to be taken into account, merging all the sensory modalities of the user into a multimodal answer. The global objective of my research activities is to improve 3D interaction with complex virtual environments by proposing novel approaches for physically-based and multimodal interaction. I have laid the foundations of my work on designing the interactions with complex virtual worlds, referring to a higher demand in the characteristics of the virtual environments. My research could be described within three main research axes inherent to the 3D interaction loop: (1) the physically-based modeling of the virtual world to take into account the complexity of the virtual object behavior, their topology modifications as well as their interactions, (2) the multimodal feedback for combining the sensory modalities into a global answer from the virtual world to the user and (3) the design of body-based 3D interaction techniques and devices for establishing the interfaces between the user and the virtual world. All these contributions could be gathered in a general framework within the 3D interaction loop. By improving all the components of this framework, I aim at proposing approaches that could be used in future virtual reality applications but also more generally in other areas such as medical simulation, gesture training, robotics, virtual prototyping for the industry or web contents.Le virtuel est devenu un vaste champ d'exploration pour la recherche et offre de nos jours de nombreuses possibilités : assister le chirurgien, réaliser des prototypes de pièces industrielles, simuler des phénomènes naturels, remonter dans le temps ou proposer des applications ludiques aux utilisateurs au travers de jeux ou de films. Bien plus que le rendu purement visuel d'environnement virtuel, la réalité virtuelle aspire à -littéralement- immerger l'utilisateur dans le monde virtuel. L'utilisateur peut ainsi interagir avec le contenu numérique et percevoir les effets de ses actions au travers de différents retours sensoriels. Permettre une véritable immersion de l'utilisateur dans des environnements virtuels de plus en plus complexes confronte la recherche en réalité virtuelle à des défis importants: les gestes de l'utilisateur doivent être capturés puis directement transmis au monde virtuel afin de le modifier en temps-réel. Les retours sensoriels ne sont pas uniquement visuels mais doivent être combinés avec les retours auditifs ou haptiques dans une réponse globale multimodale. L'objectif principal de mes activités de recherche consiste à améliorer l'interaction 3D avec des environnements virtuels complexes en proposant de nouvelles approches utilisant la simulation physique et exploitant au mieux les différentes modalités sensorielles. Dans mes travaux, je m'intéresse tout particulièrement à concevoir des interactions avec des mondes virtuels complexes. Mon approche peut être décrite au travers de trois axes principaux de recherche: (1) la modélisation dans les mondes virtuels d'environnements physiques plausibles où les objets réagissent de manière naturelle, même lorsque leur topologie est modifiée ou lorsqu'ils sont en interaction avec d'autres objets, (2) la mise en place de retours sensoriels multimodaux vers l'utilisateur intégrant des composantes visuelles, haptiques et/ou sonores, (3) la prise en compte de l'interaction physique de l'utilisateur avec le monde virtuel dans toute sa richesse : mouvements de la tête, des deux mains, des doigts, des jambes, voire de tout le corps, en concevant de nouveaux dispositifs ou de nouvelles techniques d'interactions 3D. Les différentes contributions que j'ai proposées dans chacun de ces trois axes peuvent être regroupées au sein d'un cadre plus général englobant toute la boucle d'interaction 3D avec les environnements virtuels. Elles ouvrent des perspectives pour de futures applications en réalité virtuelle mais également plus généralement dans d'autres domaines tels que la simulation médicale, l'apprentissage de gestes, la robotique, le prototypage virtuel pour l'industrie ou bien les contenus web

3D Scene Reconstruction with Micro-Aerial Vehicles and Mobile Devices

Scene reconstruction is the process of building an accurate geometric model of one\u27s environment from sensor data. We explore the problem of real-time, large-scale 3D scene reconstruction in indoor environments using small laser range-finders and low-cost RGB-D (color plus depth) cameras. We focus on computationally-constrained platforms such as micro-aerial vehicles (MAVs) and mobile devices. These platforms present a set of fundamental challenges - estimating the state and trajectory of the device as it moves within its environment and utilizing lightweight, dynamic data structures to hold the representation of the reconstructed scene. The system needs to be computationally and memory-efficient, so that it can run in real time, onboard the platform. In this work, we present three scene reconstruction systems. The first system uses a laser range-finder and operates onboard a quadrotor MAV. We address the issues of autonomous control, state estimation, path-planning, and teleoperation. We propose the multi-volume occupancy grid (MVOG) - a novel data structure for building 3D maps from laser data, which provides a compact, probabilistic scene representation. The second system uses an RGB-D camera to recover the 6-DoF trajectory of the platform by aligning sparse features observed in the current RGB-D image against a model of previously seen features. We discuss our work on camera calibration and the depth measurement model. We apply the system onboard an MAV to produce occupancy-based 3D maps, which we utilize for path-planning. Finally, we present our contributions to a scene reconstruction system for mobile devices with built-in depth sensing and motion-tracking capabilities. We demonstrate reconstructing and rendering a global mesh on the fly, using only the mobile device\u27s CPU, in very large (300 square meter) scenes, at a resolutions of 2-3cm. To achieve this, we divide the scene into spatial volumes indexed by a hash map. Each volume contains the truncated signed distance function for that area of space, as well as the mesh segment derived from the distance function. This approach allows us to focus computational and memory resources only in areas of the scene which are currently observed, as well as leverage parallelization techniques for multi-core processing

Fusion of interventional ultrasound & X-ray

In einer immer älter werdenden Bevölkerung wird die Behandlung von strukturellen Herzkrankheiten zunehmend wichtiger. Verbesserte medizinische Bildgebung und die Einführung neuer Kathetertechnologien führten dazu, dass immer mehr herkömmliche chirurgische Eingriffe am offenen Herzen durch minimal invasive Methoden abgelöst werden. Diese modernen Interventionen müssen durch verschiedenste Bildgebungsverfahren navigiert werden. Hierzu werden hauptsächlich Röntgenfluoroskopie und transösophageale Echokardiografie (TEE) eingesetzt. Röntgen bietet eine gute Visualisierung der eingeführten Katheter, was essentiell für eine gute Navigation ist. TEE hingegen bietet die Möglichkeit der Weichteilgewebedarstellung und kann damit vor allem zur Darstellung von anatomischen Strukturen, wie z.B. Herzklappen, genutzt werden. Beide Modalitäten erzeugen Bilder in Echtzeit und werden für die erfolgreiche Durchführung minimal invasiver Herzchirurgie zwingend benötigt. Üblicherweise sind beide Systeme eigenständig und nicht miteinander verbunden. Es ist anzunehmen, dass eine Bildfusion beider Welten einen großen Vorteil für die behandelnden Operateure erzeugen kann, vor allem eine verbesserte Kommunikation im Behandlungsteam. Ebenso können sich aus der Anwendung heraus neue chirurgische Worfklows ergeben. Eine direkte Fusion beider Systeme scheint nicht möglich, da die Bilddaten eine zu unterschiedliche Charakteristik aufweisen. Daher kommt in dieser Arbeit eine indirekte Registriermethode zum Einsatz. Die TEE-Sonde ist während der Intervention ständig im Fluoroskopiebild sichtbar. Dadurch wird es möglich, die Sonde im Röntgenbild zu registrieren und daraus die 3D Position abzuleiten. Der Zusammenhang zwischen Ultraschallbild und Ultraschallsonde wird durch eine Kalibrierung bestimmt. In dieser Arbeit wurde die Methode der 2D-3D Registrierung gewählt, um die TEE Sonde auf 2D Röntgenbildern zu erkennen. Es werden verschiedene Beiträge präsentiert, welche einen herkömmlichen 2D-3D Registrieralgorithmus verbessern. Nicht nur im Bereich der Ultraschall-Röntgen-Fusion, sondern auch im Hinblick auf allgemeine Registrierprobleme. Eine eingeführte Methode ist die der planaren Parameter. Diese verbessert die Robustheit und die Registriergeschwindigkeit, vor allem während der Registrierung eines Objekts aus zwei nicht-orthogonalen Richtungen. Ein weiterer Ansatz ist der Austausch der herkömmlichen Erzeugung von sogenannten digital reconstructed radiographs. Diese sind zwar ein integraler Bestandteil einer 2D-3D Registrierung aber gleichzeitig sehr zeitaufwendig zu berechnen. Es führt zu einem erheblichen Geschwindigkeitsgewinn die herkömmliche Methode durch schnelles Rendering von Dreiecksnetzen zu ersetzen. Ebenso wird gezeigt, dass eine Kombination von schnellen lernbasierten Detektionsalgorithmen und 2D-3D Registrierung die Genauigkeit und die Registrierreichweite verbessert. Zum Abschluss werden die ersten Ergebnisse eines klinischen Prototypen präsentiert, welcher die zuvor genannten Methoden verwendet.Today, in an elderly community, the treatment of structural heart disease will become more and more important. Constant improvements of medical imaging technologies and the introduction of new catheter devices caused the trend to replace conventional open heart surgery by minimal invasive interventions. These advanced interventions need to be guided by different medical imaging modalities. The two main imaging systems here are X-ray fluoroscopy and Transesophageal  Echocardiography (TEE). While X-ray provides a good visualization of inserted catheters, which is essential for catheter navigation, TEE can display soft tissues, especially anatomical structures like heart valves. Both modalities provide real-time imaging and are necessary to lead minimal invasive heart surgery to success. Usually, the two systems are detached and not connected. It is conceivable that a fusion of both worlds can create a strong benefit for the physicians. It can lead to a better communication within the clinical team and can probably enable new surgical workflows. Because of the completely different characteristics of the image data, a direct fusion seems to be impossible. Therefore, an indirect registration of Ultrasound and X-ray images is used. The TEE probe is usually visible in the X-ray image during the described minimal-invasive interventions. Thereby, it becomes possible to register the TEE probe in the fluoroscopic images and to establish its 3D position. The relationship of the Ultrasound image to the Ultrasound probe is known by calibration. To register the TEE probe on 2D X-ray images, a 2D-3D registration approach is chosen in this thesis. Several contributions are presented, which are improving the common 2D-3D registration algorithm for the task of Ultrasound and X-ray fusion, but also for general 2D-3D registration problems. One presented approach is the introduction of planar parameters that increase robustness and speed during the registration of an object on two non-orthogonal views. Another approach is to replace the conventional generation of digital reconstructedradiographs, which is an integral part of 2D-3D registration but also a performance bottleneck, with fast triangular mesh rendering. This will result in a significant performance speed-up. It is also shown that a combination of fast learning-based detection algorithms with 2D-3D registration will increase the accuracy and the capture range, instead of employing them solely to the  registration/detection of a TEE probe. Finally, a first clinical prototype is presented which employs the presented approaches and first clinical results are shown

Ανάπτυξη τεχνολογιών επαυξημένης πραγματικότητας στην ιατρική εκπαίδευση με προσομοιωτές

Στην παρούσα διδακτορική διατριβή παρουσιάζουμε ένα πρωτοπόρο σύστημα εκπαίδευσης και αξιολόγησης βασικών δεξιοτήτων λαπαροσκοπικής χειρουργικής σε περιβάλλον Επαυξημένης Πραγματικότητας (ΕΠ). Το προτεινόμενο σύστημα αποτελεί μια πλήρως λειτουργική πλατφόρμα εκπαίδευσης η οποία επιτρέπει σε χειρουργούς να εξασκηθούν χρησιμοποιώντας πραγματικά λαπαροσκοπικά εργαλεία και αλληλεπιδρώντας με ψηφιακά αντικείμενα εντός ενός πραγματικού περιβάλλοντος εκπαίδευσης. Το σύστημα αποτελείται από ένα τυπικό κουτί λαπαροσκοπικής εκπαίδευσης, πραγματικά χειρουργικά εργαλεία, κάμερα και συστοιχία αισθητήρων που επιτρέπουν την ανίχνευση και καταγραφή των κινήσεων του χειρουργού σε πραγματικό χρόνο. Χρησιμοποιώντας το προτεινόμενο σύστημα, σχεδιάσαμε και υλοποιήσαμε σενάρια εκπαίδευσης παρόμοια με τις ασκήσεις του προγράμματος FLS®, στοχεύοντας σε δεξιότητες όπως η αίσθηση βάθους, ο συντονισμός χεριού-ματιού, και η παράλληλη χρήση δύο χεριών. Επιπλέον των βασικών δεξιοτήτων, το προτεινόμενο σύστημα χρησιμοποιήθηκε για τον σχεδιασμό σεναρίου εξάσκησης διαδικαστικών δεξιοτήτων, οι οποίες περιλάμβανουν την εφαρμογή χειρουργικών clips καθώς και την απολίνωση εικονικής αρτηρίας, σε περιβάλλον ΕΠ. Τα αποτελέσματα συγκριτικών μελετών μεταξύ έμπειρων και αρχαρίων χειρουργών που πραγματοποιήθηκαν στα πλαίσια της παρούσας διατριβής υποδηλώνουν την εγκυρότητα του προτεινόμενου συστήματος. Επιπλέον, εξήχθησαν σημαντικά συμπεράσματα σχετικά με την πιθανή χρήση της ΕΑ στην λαπαροσκοπική προσομοίωση. Η συγκεκριμένη τεχνολογία προσφέρει αυξημένη αίσθηση οπτικού ρεαλισμού και ευελιξία στον σχεδιασμό εκπαιδευτικών σεναρίων, παρουσιάζοντας σημαντικά μικρότερες απαιτήσεις από πλευράς εξοπλισμού σε σύγκριση με τις υπάρχουσες εμπορικές πλατφόρμες. Βάσει των αποτελεσμάτων της παρούσας διατριβής μπορεί με ασφάλεια να εξαχθεί το συμπέρασμα πως η ΕΠ αποτελεί μια πολλά υποσχόμενη τεχνολογία που θα μπορούσε να χρησιμοποιηθεί για τον σχεδιασμό προσομοιωτών λαπαροσκοπικής χειρουργικής ως εναλλακτική των υπαρχόντων τεχνολογιών και συστημάτων.In this thesis we present what is, to the best of our knowledge, the first framework for training and assessment of fundamental psychomotor and procedural laparoscopic skills in an interactive Augmented Reality (AR) environment. The proposed system is a fully-featured laparoscopic training platform, allowing surgeons to practice by manipulating real instruments while interacting with virtual objects within a real environment. It consists of a standard laparoscopic box-trainer, real instruments, a camera and a set of sensory devices for real-time tracking of surgeons’ actions. The proposed framework has been used for the implementation of AR-based training scenarios similar to the drills of the FLS® program, focusing on fundamental laparoscopic skills such as depth-perception, hand-eye coordination and bimanual operation. Moreover, this framework allowed the implementation of a proof-of-concept procedural skills training scenario, which involved clipping and cutting of a virtual artery within an AR environment. Comparison studies conducted for the evaluation of the presented framework indicated high content and face validity. In addition, significant conclusions regarding the potentials of introducing AR in laparoscopic simulation training and assessment were drawn. This technology provides an advanced sense of visual realism combined with a great flexibility in training task prototyping, with minimum requirements in terms of hardware as compared to commercially available platforms. Thereby, it can be safely stated that AR is a promising technology which can indeed provide a valuable alternative to the training modalities currently used in MIS

Proceedings of the Third International Workshop on Mathematical Foundations of Computational Anatomy - Geometrical and Statistical Methods for Modelling Biological Shape Variability

International audienceComputational anatomy is an emerging discipline at the interface of geometry, statistics and image analysis which aims at modeling and analyzing the biological shape of tissues and organs. The goal is to estimate representative organ anatomies across diseases, populations, species or ages, to model the organ development across time (growth or aging), to establish their variability, and to correlate this variability information with other functional, genetic or structural information. The Mathematical Foundations of Computational Anatomy (MFCA) workshop aims at fostering the interactions between the mathematical community around shapes and the MICCAI community in view of computational anatomy applications. It targets more particularly researchers investigating the combination of statistical and geometrical aspects in the modeling of the variability of biological shapes. The workshop is a forum for the exchange of the theoretical ideas and aims at being a source of inspiration for new methodological developments in computational anatomy. A special emphasis is put on theoretical developments, applications and results being welcomed as illustrations. Following the successful rst edition of this workshop in 20061 and second edition in New-York in 20082, the third edition was held in Toronto on September 22 20113. Contributions were solicited in Riemannian and group theoretical methods, geometric measurements of the anatomy, advanced statistics on deformations and shapes, metrics for computational anatomy, statistics of surfaces, modeling of growth and longitudinal shape changes. 22 submissions were reviewed by three members of the program committee. To guaranty a high level program, 11 papers only were selected for oral presentation in 4 sessions. Two of these sessions regroups classical themes of the workshop: statistics on manifolds and diff eomorphisms for surface or longitudinal registration. One session gathers papers exploring new mathematical structures beyond Riemannian geometry while the last oral session deals with the emerging theme of statistics on graphs and trees. Finally, a poster session of 5 papers addresses more application oriented works on computational anatomy