Littérature scientifique sur le sujet « Robotized Tomography »

Abstract BACKGROUND: Operating microscopes are essential for most neurosurgical procedures. Modern robot-assisted controls offer new possibilities, combining the advantages of conventional and automated systems. OBJECTIVE: We evaluated the prototype of a completely robotized operating microscope with an integrated optical coherence tomography module. METHODS: A standard operating microscope was fitted with motors and control instruments, with the manual control mode and balance preserved. In the robot mode, the microscope was steered by a remote control that could be fixed to a surgical instrument. External encoders and accelerometers tracked microscope movements. The microscope was additionally fitted with an optical coherence tomography-scanning module. RESULTS: The robotized microscope was tested on model systems. It could be freely positioned, without forcing the surgeon to take the hands from the instruments or avert the eyes from the oculars. Positioning error was about 1 mm, and vibration faded in 1 second. Tracking of microscope movements, combined with an autofocus function, allowed determination of the focus position within the 3-dimensional space. This constituted a second loop of navigation independent from conventional infrared reflector-based techniques. In the robot mode, automated optical coherence tomography scanning of large surface areas was feasible. CONCLUSION: The prototype of a robotized optical coherence tomography-integrated operating microscope combines the advantages of a conventional manually controlled operating microscope with a remote-controlled positioning aid and a self-navigating microscope system that performs automated positioning tasks such as surface scans. This demonstrates that, in the future, operating microscopes may be used to acquire intraoperative spatial data, volume changes, and structural data of brain or brain tumor tissue.

Abstract BACKGROUND Robotic technologies have been used in the neurosurgical operating rooms for the last 30 yr. They have been adopted for several stereotactic applications and, particularly, image-guided biopsy of intracranial lesions which are not amenable for open surgical resection. OBJECTIVE To assess feasibility, safety, accuracy, and diagnostic yield of robot-assisted frameless stereotactic brain biopsy with a recently introduced miniaturized device (iSYS1; Interventional Systems Medizintechnik GmbH, Kitzbühel, Austria), fixed to the Mayfield headholder by a jointed arm. METHODS Clinical and surgical data of all patients undergoing frameless stereotactic biopsies using the iSYS1 robotized system from October 2016 to December 2017 have been prospectively collected and analyzed. Facial surface registration has been adopted for optical neuronavigation. RESULTS Thirty-nine patients were included in the study. Neither mortality nor morbidity related to the surgical procedure performed with the robot was recorded. Diagnostic tissue samples were obtained in 38 out of 39 procedures (diagnostic yield per procedure was 97.4%). All patients received a definitive histological diagnosis. Mean target error was 1.06 mm (median 1 mm, range 0.1-4 mm). CONCLUSION The frameless robotic iSYS1-assisted biopsy technique was determined to be feasible, safe, and accurate procedure; moreover, the diagnostic yield was high. The surface matching registration method with computed tomography as the reference image set did not negatively affect the accuracy of the procedure.

Abstract Robot positioning performance is studied in the scope of a robotized X-ray computed tomography application on a ABB IRB4600 robot. The robot has the “absolute accuracy” option, that is, the manufacturer has identified the manufacturing defects and included them in the robot control. Laser-tracker measurement on a 6.5-h long linear trajectory shows thermal drift and backlash issues, affecting the positioning unidirectional repeatability and bidirectional accuracy. A thermo-geometrical model with backlash compensation is developed. Geometrical calibration improves the forwards unidirectional mean accuracy from 1.39 to 0.06 mm between theoretical and optimized geometrical parameters with a stable thermal state. Thermo-geometrical calibration reduces the positioning scattering from a maximum of 0.15 to 0.05 mm (close to the repeatability of the robot). Backlash compensation improves the bidirectional mean accuracy from 1.53 to 0.07 mm.

Clinical imaging developed quickly to assume an imperative part in the conclusion and treatment of an illness. Robotized examination of clinical picture examination has expanded successfully using profound learning procedures to get much speedier groupings once prepared and learn significant highlights for explicit assignments, demonstrated to be assessable in clinical practice and an important device to help dynamic in the clinical field. Inside Opthalmology, Optical Coherence Tomography (OCT) is a volumetric imaging methodology that purposes the conclusion, observing, and estimating reaction to treatment in the eyes. Early discovery of eyes sicknesses including Diabetic Macular Edema (DME) is crucial interaction to keep away from confusion like visual impairment. This work utilized a profound convolutional brain organization (CNN) based technique for the DME order tasks. To exhibit the effect of convolutional, five models with various Convolutional layers were assembled then the best one chose given assessment measurements. The exactness of the model improved while expanding the quantity of Convolutional Layers and accomplished 82% by 5-Convolutional Layer, Precision and Recall of the CNN model per DME class were 87%% and 74%, individually. These outcomes featured the capability of profound learning in helping dynamics in patients with DME.

La tomographie par rayons X ou CT pour "Computed Tomography" est un outil puissant pour caractériser et localiser les défauts internes et pour vérifier la conformité géométrique d’un objet. Contrairement au cas des applications médicales, l’objet inspecté en Contrôle Non Destructif (CND) peut être très grand et composé de matériaux de haute atténuation, auquel cas l’utilisation d’une trajectoire circulaire pour l’inspection est impossible à cause de contraintes dans l’espace. Pour cette raison, l’utilisation de bras robotisés est l’une des nouvelles tendances reconnues dans la CT, car elle autorise plus de flexibilité dans la trajectoire d’acquisition et permet donc la reconstruction 3D de régions difficilement accessibles dont la reconstruction ne pourrait pas être assurée par des systèmes de tomographie industriels classiques. Une cellule de tomographie X robotisée a été installée au CEA. La plateforme se compose de deux bras robotiques pour positionner et déplacer la source et le détecteur en vis-à-vis. Parmi les nouveaux défis posés par la tomographie robotisée, nous nous concentrons ici plus particulièrement sur la limitation de l’ouverture angulaire imposée par la configuration en raison des contraintes importantes sur le mouvement mécanique de la plateforme. Le deuxième défi majeur est la troncation des projections qui se produit lorsque l’objet est trop grand par rapport au détecteur. L’objectif principal de ce travail consiste à adapter et à optimiser des méthodes de reconstruction CT pour des trajectoires non standard. Nous étudions à la fois des algorithmes de reconstruction analytiques et itératifs. Avant d’effectuer des inspections robotiques réelles, nous comptons sur des simulations numériques pour évaluer les performances des algorithmes de reconstruction sur des configurations d’acquisition de données. Pour ce faire, nous utilisons CIVA, qui est un outil de simulation pour le CND développé au CEA et qui est capable de simuler des données de projections réalistes correspondant à des configurations d’acquisition définies par l’utilisateur
X-ray computed tomography (CT) is a powerful tool to characterize or localize inner flaws and to verify the geometric conformity of an object. In contrast to medical applications, the scanned object in non-destructive testing (NDT) might be very large and composed of high-attenuation materials and consequently the use of a standard circular trajectory for data acquisition would be impossible due to constraints in space. For this reason, the use of robotic arms is one of the acknowledged new trends in NDT since it allows more flexibility in acquisition trajectories and therefore could be used for 3D reconstruction of hardly accessible regions that might be a major limitation of classical CT systems. A robotic X-ray inspection platform has been installed at CEA LIST. The considered system integrates two robots that move the X-ray generator and detector. Among the new challenges brought by robotic CT, we focus in this thesis more particularly on the limited access viewpoint imposed by the setup where important constraints control the mechanical motion of the platform. The second major challenge is the truncation of projections that occur when only a field-of-view (FOV) of the object is viewed by the detector. Before performing real robotic inspections, we highly rely on CT simulations to evaluate the capability of the reconstruction algorithm corresponding to a defined scanning trajectory and data acquisition configuration. For this purpose, we use CIVA which is an advanced NDT simulation platform developed at CEA and that can provide a realistic model for radiographic acquisitions and is capable of simulating the projection data corresponding to a specific CT scene defined by the user. Thus, the main objective of this thesis is to develop analytical and iterative reconstruction algorithms adapted to nonstandard trajectories and to integrate these algorithms in CIVA software as plugins of reconstruction

Il manque actuellement aux médecins une nouvelle méthode qui rationalise le traitement peu invasif pour en faire des procédures à opérateur unique, assistées par une caractérisation précise des tissus in situ et en temps réel, en situation de prise de décisions dans la gestion du cancer colorectal. Une solution prometteuse à ce problème a été développée par l'équipe AVR (Automatique, Vision et Robotique) du laboratoire ICube, au sein de laquelle l'endoscope interventionnel flexible (fabriqué par Karl Storz) a été entièrement robotisé, permettant ainsi à un seul opérateur de télémanipuler indépendamment l'endoscope et deux instruments thérapeutiques insérables, grâce à unité de contrôle commune. Cependant, l'endoscope flexible assisté par robot est soumis aux mêmes limites de précision diagnostique que les systèmes d'endoscopie standards. Il a été démontré que l'OCT endoscopique présente un potentiel pour l'imagerie des troubles de la voie gastro-intestinale et pour la différenciation de tissus sains des tissus malades. Actuellement, l'OCT se limite à l'imagerie de l'œsophage humain, qui présente une géométrie simple et un accès facile. Ni l'OCT, ni l'endoscope robotisé ne peuvent résoudre à eux seuls les limites de la norme actuelle de soins pour la prise en charge d’un cancer du côlon. La combinaison de ces deux technologies et le développement d'une nouvelle plate-forme pour la détection et le traitement précoce du cancer constituent l'objet principal de cette thèse, avec la vision de développer une console d'imagerie OCT et une sonde de haute technologie intégrée à l'endoscope robotisé. Ce système permet d'obtenir des images de l'intérieur du gros intestin pour la caractérisation des tissus et l'assistance au traitement, permettant ainsi à un seul opérateur d'effectuer une intervention peu invasive en mode télémanipulation
There exists an unmet clinical need to provide doctors with a new method that streamlines minimally invasive endoscopic treatment of colorectal cancer to single operator procedures assisted by in-situ and real-time accurate tissue characterization for informed treatment decisions. A promising solution to this problem has been developed at the ICube laboratory, in which the flexible interventional endoscope (Karl Storz) was completely robotized, so allowing a single operator to independently telemanipulate the endoscope and two insertable therapeutic instruments with a joint control unit. However, the robot-assisted flexible endoscope is subject to the same diagnostic accuracy limitations as standard endoscopy systems. It has been demonstrated that endoscopic optical coherence tomography (OCT) has a good potential for imaging disorders in the gastrointestinal tract and differentiating healthy tissue from diseased. Neither OCT, nor the robotized endoscope can solve the limitations of current standard of care for colon cancer management alone. Combining these two technologies and developing a new platform for early detection and treatment of cancer is the main interest of this work, with the aim of developing a state-of-the-art OCT imaging console and probe integrated with the robotized endoscope. The capabilities of this new technology for imaging of the interior of the large intestine were tested in pre-clinical experiments showing potential for improvement in margin verification during minimally invasive endoscopic treatment in the telemanipulation mode

La thèse explore l’automatisation de la tomographie robotisée pour l’analyse de grandes pièces, un défi clé dans les secteurs industriels comme l’aéronautique et l’énergie. L’objectif principal est de surmonter deux obstacles majeurs : la faisabilité des trajectoires dans des espaces de configuration complexes et l’ordonnancement des tâches robotiques, tout en répondant aux contraintes de synchronisation stricte et d’évitement des collisions. La première contribution repose sur une méthode innovante utilisant la décomposition en pavés [x]-contractiles, combinant analyse par intervalles et théorie des graphes. Cette approche permet de calculer efficacement le nombre de composantes connexes dans les espaces de configuration, offrant une amélioration significative de la complexité computationnelle par rapport aux techniques conventionnelles. La seconde contribution introduit l’algorithme MaxMatRTSP, spécialement conçu pour coordonner deux robots dans un environnement tomographique. Cet algorithme intègre simultanément la planification de trajectoires et l’ordonnancement des tâches, en prenant en compte les contraintes industrielles spécifiques. Validé à travers des simulations et des expérimentations sur un système réel, il a démontré des performances supérieures aux méthodes actuelles
The thesis explores the automation of robotic tomography for the analysis of large parts, a key challenge in industrial sectors such as aerospace and energy. The primary objective is to overcome two major obsta cles: the feasibility of trajectories in complex configuration spaces and the scheduling of robotic tasks, while addressing strict synchronization and collision avoidance constraints. The first contribution is based on an innovative method that employs decomposition into [x]-contractible tiles, combining interval analysis and graph theory. This approach efficiently calculates the number of connected components in configuration spaces, offering a significant improvement in computational complexity compared to state of the art techniques. The second contribution introduces the Max-MatRTSP algorithm, specifically designed to coordinate two robots in a tomographic environment. This algorithm simultaneously integrates trajectory planning and task scheduling, accounting for specific industrial con straints. Validated through simulations and ex- periments on real systems, it has demon strated superior performance compared to existing methods

In this paper, a new robotized needle insertion device is proposed for computer-assisted percutaneous therapy. The insertion device is integrated in a robotic system dedicated to gesture guidance in a Computed Tomography (CT) scan. The presented design fulfills the stringent requirements of such a medical application: compatibility with a CT-scan and haptic control by the practitioner are ensured as well as safety and sterilization. The novel design of the insertion device is first presented, outlining its main properties, before introducing preliminary experimental results.