Optimised Calibration, Registration and Tracking for Image Enhanced Surgical Navigation in ENT Operations

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Optimised calibration, registration and tracking for image enhanced surgical navigation in ENT operations

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of an augmented reality guided computer assisted orthopaedic surgery system

Previously held under moratorium from 1st December 2016 until 1st December 2021.This body of work documents the developed of a proof of concept augmented reality guided computer assisted orthopaedic surgery system – ARgCAOS. After initial investigation a visible-spectrum single camera tool-mounted tracking system based upon fiducial planar markers was implemented. The use of visible-spectrum cameras, as opposed to the infra-red cameras typically used by surgical tracking systems, allowed the captured image to be streamed to a display in an intelligible fashion. The tracking information defined the location of physical objects relative to the camera. Therefore, this information allowed virtual models to be overlaid onto the camera image. This produced a convincing augmented experience, whereby the virtual objects appeared to be within the physical world, moving with both the camera and markers as expected of physical objects. Analysis of the first generation system identified both accuracy and graphical inadequacies, prompting the development of a second generation system. This too was based upon a tool-mounted fiducial marker system, and improved performance to near-millimetre probing accuracy. A resection system was incorporated into the system, and utilising the tracking information controlled resection was performed, producing sub-millimetre accuracies. Several complications resulted from the tool-mounted approach. Therefore, a third generation system was developed. This final generation deployed a stereoscopic visible-spectrum camera system affixed to a head-mounted display worn by the user. The system allowed the augmentation of the natural view of the user, providing convincing and immersive three dimensional augmented guidance, with probing and resection accuracies of 0.55±0.04 and 0.34±0.04 mm, respectively.This body of work documents the developed of a proof of concept augmented reality guided computer assisted orthopaedic surgery system – ARgCAOS. After initial investigation a visible-spectrum single camera tool-mounted tracking system based upon fiducial planar markers was implemented. The use of visible-spectrum cameras, as opposed to the infra-red cameras typically used by surgical tracking systems, allowed the captured image to be streamed to a display in an intelligible fashion. The tracking information defined the location of physical objects relative to the camera. Therefore, this information allowed virtual models to be overlaid onto the camera image. This produced a convincing augmented experience, whereby the virtual objects appeared to be within the physical world, moving with both the camera and markers as expected of physical objects. Analysis of the first generation system identified both accuracy and graphical inadequacies, prompting the development of a second generation system. This too was based upon a tool-mounted fiducial marker system, and improved performance to near-millimetre probing accuracy. A resection system was incorporated into the system, and utilising the tracking information controlled resection was performed, producing sub-millimetre accuracies. Several complications resulted from the tool-mounted approach. Therefore, a third generation system was developed. This final generation deployed a stereoscopic visible-spectrum camera system affixed to a head-mounted display worn by the user. The system allowed the augmentation of the natural view of the user, providing convincing and immersive three dimensional augmented guidance, with probing and resection accuracies of 0.55±0.04 and 0.34±0.04 mm, respectively

A continuum robotic platform for endoscopic non-contact laser surgery: design, control, and preclinical evaluation

The application of laser technologies in surgical interventions has been accepted in the clinical domain due to their atraumatic properties. In addition to manual application of fibre-guided lasers with tissue contact, non-contact transoral laser microsurgery (TLM) of laryngeal tumours has been prevailed in ENT surgery. However, TLM requires many years of surgical training for tumour resection in order to preserve the function of adjacent organs and thus preserve the patient’s quality of life. The positioning of the microscopic laser applicator outside the patient can also impede a direct line-of-sight to the target area due to anatomical variability and limit the working space. Further clinical challenges include positioning the laser focus on the tissue surface, imaging, planning and performing laser ablation, and motion of the target area during surgery. This dissertation aims to address the limitations of TLM through robotic approaches and intraoperative assistance. Although a trend towards minimally invasive surgery is apparent, no highly integrated platform for endoscopic delivery of focused laser radiation is available to date. Likewise, there are no known devices that incorporate scene information from endoscopic imaging into ablation planning and execution. For focusing of the laser beam close to the target tissue, this work first presents miniaturised focusing optics that can be integrated into endoscopic systems. Experimental trials characterise the optical properties and the ablation performance. A robotic platform is realised for manipulation of the focusing optics. This is based on a variable-length continuum manipulator. The latter enables movements of the endoscopic end effector in five degrees of freedom with a mechatronic actuation unit. The kinematic modelling and control of the robot are integrated into a modular framework that is evaluated experimentally. The manipulation of focused laser radiation also requires precise adjustment of the focal position on the tissue. For this purpose, visual, haptic and visual-haptic assistance functions are presented. These support the operator during teleoperation to set an optimal working distance. Advantages of visual-haptic assistance are demonstrated in a user study. The system performance and usability of the overall robotic system are assessed in an additional user study. Analogous to a clinical scenario, the subjects follow predefined target patterns with a laser spot. The mean positioning accuracy of the spot is 0.5 mm. Finally, methods of image-guided robot control are introduced to automate laser ablation. Experiments confirm a positive effect of proposed automation concepts on non-contact laser surgery.Die Anwendung von Lasertechnologien in chirurgischen Interventionen hat sich aufgrund der atraumatischen Eigenschaften in der Klinik etabliert. Neben manueller Applikation von fasergeführten Lasern mit Gewebekontakt hat sich die kontaktfreie transorale Lasermikrochirurgie (TLM) von Tumoren des Larynx in der HNO-Chirurgie durchgesetzt. Die TLM erfordert zur Tumorresektion jedoch ein langjähriges chirurgisches Training, um die Funktion der angrenzenden Organe zu sichern und damit die Lebensqualität der Patienten zu erhalten. Die Positionierung des mikroskopis chen Laserapplikators außerhalb des Patienten kann zudem die direkte Sicht auf das Zielgebiet durch anatomische Variabilität erschweren und den Arbeitsraum einschränken. Weitere klinische Herausforderungen betreffen die Positionierung des Laserfokus auf der Gewebeoberfläche, die Bildgebung, die Planung und Ausführung der Laserablation sowie intraoperative Bewegungen des Zielgebietes. Die vorliegende Dissertation zielt darauf ab, die Limitierungen der TLM durch robotische Ansätze und intraoperative Assistenz zu adressieren. Obwohl ein Trend zur minimal invasiven Chirurgie besteht, sind bislang keine hochintegrierten Plattformen für die endoskopische Applikation fokussierter Laserstrahlung verfügbar. Ebenfalls sind keine Systeme bekannt, die Szeneninformationen aus der endoskopischen Bildgebung in die Ablationsplanung und -ausführung einbeziehen. Für eine situsnahe Fokussierung des Laserstrahls wird in dieser Arbeit zunächst eine miniaturisierte Fokussieroptik zur Integration in endoskopische Systeme vorgestellt. Experimentelle Versuche charakterisieren die optischen Eigenschaften und das Ablationsverhalten. Zur Manipulation der Fokussieroptik wird eine robotische Plattform realisiert. Diese basiert auf einem längenveränderlichen Kontinuumsmanipulator. Letzterer ermöglicht in Kombination mit einer mechatronischen Aktuierungseinheit Bewegungen des Endoskopkopfes in fünf Freiheitsgraden. Die kinematische Modellierung und Regelung des Systems werden in ein modulares Framework eingebunden und evaluiert. Die Manipulation fokussierter Laserstrahlung erfordert zudem eine präzise Anpassung der Fokuslage auf das Gewebe. Dafür werden visuelle, haptische und visuell haptische Assistenzfunktionen eingeführt. Diese unterstützen den Anwender bei Teleoperation zur Einstellung eines optimalen Arbeitsabstandes. In einer Anwenderstudie werden Vorteile der visuell-haptischen Assistenz nachgewiesen. Die Systemperformanz und Gebrauchstauglichkeit des robotischen Gesamtsystems werden in einer weiteren Anwenderstudie untersucht. Analog zu einem klinischen Einsatz verfolgen die Probanden mit einem Laserspot vorgegebene Sollpfade. Die mittlere Positioniergenauigkeit des Spots beträgt dabei 0,5 mm. Zur Automatisierung der Ablation werden abschließend Methoden der bildgestützten Regelung vorgestellt. Experimente bestätigen einen positiven Effekt der Automationskonzepte für die kontaktfreie Laserchirurgie

AUGMENTED REALITY AND INTRAOPERATIVE C-ARM CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED ROBOTIC SURGERY

Minimally-invasive robotic-assisted surgery is a rapidly-growing alternative to traditionally open and laparoscopic procedures; nevertheless, challenges remain. Standard of care derives surgical strategies from preoperative volumetric data (i.e., computed tomography (CT) and magnetic resonance (MR) images) that benefit from the ability of multiple modalities to delineate different anatomical boundaries. However, preoperative images may not reflect a possibly highly deformed perioperative setup or intraoperative deformation. Additionally, in current clinical practice, the correspondence of preoperative plans to the surgical scene is conducted as a mental exercise; thus, the accuracy of this practice is highly dependent on the surgeon’s experience and therefore subject to inconsistencies. In order to address these fundamental limitations in minimally-invasive robotic surgery, this dissertation combines a high-end robotic C-arm imaging system and a modern robotic surgical platform as an integrated intraoperative image-guided system. We performed deformable registration of preoperative plans to a perioperative cone-beam computed tomography (CBCT), acquired after the patient is positioned for intervention. From the registered surgical plans, we overlaid critical information onto the primary intraoperative visual source, the robotic endoscope, by using augmented reality. Guidance afforded by this system not only uses augmented reality to fuse virtual medical information, but also provides tool localization and other dynamic intraoperative updated behavior in order to present enhanced depth feedback and information to the surgeon. These techniques in guided robotic surgery required a streamlined approach to creating intuitive and effective human-machine interferences, especially in visualization. Our software design principles create an inherently information-driven modular architecture incorporating robotics and intraoperative imaging through augmented reality. The system's performance is evaluated using phantoms and preclinical in-vivo experiments for multiple applications, including transoral robotic surgery, robot-assisted thoracic interventions, and cocheostomy for cochlear implantation. The resulting functionality, proposed architecture, and implemented methodologies can be further generalized to other C-arm-based image guidance for additional extensions in robotic surgery

Stereo vision-based tracking of soft tissue motion with application to online ablation control in laser microsurgery

Recent research has revealed that image-based methods can enhance accuracy and safety in laser microsurgery. In this study, non-rigid tracking using surgical stereo imaging and its application to laser ablation is discussed. A recently developed motion estimation framework based on piecewise affine deformation modeling is extended by a mesh refinement step and considering texture information. This compensates for tracking inaccuracies potentially caused by inconsistent feature matches or drift. To facilitate online application of the method, computational load is reduced by concurrent processing and affine-invariant fusion of tracking and refinement results. The residual latency-dependent tracking error is further minimized by Kalman filter-based upsampling, considering a motion model in disparity space. Accuracy is assessed in laparoscopic, beating heart, and laryngeal sequences with challenging conditions, such as partial occlusions and significant deformation. Performance is compared with that of state-of-the-art methods. In addition, the online capability of the method is evaluated by tracking two motion patterns performed by a high-precision parallel-kinematic platform. Related experiments are discussed for tissue substitute and porcine soft tissue in order to compare performances in an ideal scenario and in a setup mimicking clinical conditions. Regarding the soft tissue trial, the tracking error can be significantly reduced from 0.72 mm to below 0.05 mm with mesh refinement. To demonstrate online laser path adaptation during ablation, the non-rigid tracking framework is integrated into a setup consisting of a surgical Er:YAG laser, a three-axis scanning unit, and a low-noise stereo camera. Regardless of the error source, such as laser-to-camera registration, camera calibration, image-based tracking, and scanning latency, the ablation root mean square error is kept below 0.21 mm when the sample moves according to the aforementioned patterns. Final experiments regarding motion-compensated laser ablation of structurally deforming tissue highlight the potential of the method for vision-guided laser surgery.EU/FP/-ICT/28866

Medical Robotics

The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

Augmented Reality Assistance for Surgical Interventions using Optical See-Through Head-Mounted Displays

Augmented Reality (AR) offers an interactive user experience via enhancing the real world environment with computer-generated visual cues and other perceptual information. It has been applied to different applications, e.g. manufacturing, entertainment and healthcare, through different AR media. An Optical See-Through Head-Mounted Display (OST-HMD) is a specialized hardware for AR, where the computer-generated graphics can be overlaid directly onto the user's normal vision via optical combiners. Using OST-HMD for surgical intervention has many potential perceptual advantages. As a novel concept, many technical and clinical challenges exist for OST-HMD-based AR to be clinically useful, which motivates the work presented in this thesis. From the technical aspects, we first investigate the display calibration of OST-HMD, which is an indispensable procedure to create accurate AR overlay. We propose various methods to reduce the user-related error, improve robustness of the calibration, and remodel the calibration as a 3D-3D registration problem. Secondly, we devise methods and develop hardware prototype to increase the user's visual acuity of both real and virtual content through OST-HMD, to aid them in tasks that require high visual acuity, e.g. dental procedures. Thirdly, we investigate the occlusion caused by the OST-HMD hardware, which limits the user's peripheral vision. We propose to use alternative indicators to remind the user of unattended environment motion. From the clinical perspective, we identified many clinical use cases where OST-HMD-based AR is potentially helpful, developed applications integrated with current clinical systems, and conducted proof-of-concept evaluations. We first present a "virtual monitor'' for image-guided surgery. It can replace real radiology monitors in the operating room with easier user control and more flexibility in positioning. We evaluated the "virtual monitor'' for simulated percutaneous spine procedures. Secondly, we developed ARssist, an application for the bedside assistant in robotic surgery. The assistant can see the robotic instruments and endoscope within the patient body with ARssist. We evaluated the efficiency, safety and ergonomics of the assistant during two typical tasks: instrument insertion and manipulation. The performance for inexperienced users is significantly improved with ARssist, and for experienced users, the system significantly enhanced their confidence level. Lastly, we developed ARAMIS, which utilizes real-time 3D reconstruction and visualization to aid the laparoscopic surgeon. It demonstrates the concept of "X-ray see-through'' surgery. Our preliminary evaluation validated the application via a peg transfer task, and also showed significant improvement in hand-eye coordination. Overall, we have demonstrated that OST-HMD based AR application provides ergonomic improvements, e.g. hand-eye coordination. In challenging situations or for novice users, the improvements in ergonomic factors lead to improvement in task performance. With continuous effort as a community, optical see-through augmented reality technology will be a useful interventional aid in the near future

Image Guidance in Telemanipulator Assisted Urology Surgery

This thesis outlines the development of an image guided surgery system, intended for use in \davinci assisted radical prostatectomy but more generally applicable to laparoscopic urology surgery. We defined the key performance parameter of the system as the accuracy of overlaying modelled anatomy onto the surgical scene. This thesis is primarily concerned with determining the system accuracy based on an analysis of the system's components. A common error measure was defined for all system components. This is an on screen error (measured in pixels) based on the error in projecting a single point lying near the apex of the prostate with the endoscope in a typical surgical pose. In this case the projected point was approximately 200 mm from the endoscope lens. An intraoperative coordinate system is first defined as the coordinate system of an optical tracking system used to track the endoscope. The MRI image of the patient is transformed into the intraoperative coordinate system. Prior to surgery the endoscope is calibrated and during surgery the endoscope is tracked, defining a transform from the coordinates of the optical tracking system to the endoscope screen. This transform is used to project the MRI image onto the endoscope video display. The early part of the thesis describes a novel algorithm for registering MRI to ultrasound images of the bone which was used to put the MRI image into the intraoperative coordinate system. Using this algorithm avoids the need for fiducial markers. The table below shows the errors (as on screen pixel RMS) due to using this algorithm. An approximate value as RMS distance error at the prostate apex point is also included

On-the-fly dense 3D surface reconstruction for geometry-aware augmented reality.

Augmented Reality (AR) is an emerging technology that makes seamless connections between virtual space and the real world by superimposing computer-generated information onto the real-world environment. AR can provide additional information in a more intuitive and natural way than any other information-delivery method that a human has ever in- vented. Camera tracking is the enabling technology for AR and has been well studied for the last few decades. Apart from the tracking problems, sensing and perception of the surrounding environment are also very important and challenging problems. Although there are existing hardware solutions such as Microsoft Kinect and HoloLens that can sense and build the environmental structure, they are either too bulky or too expensive for AR. In this thesis, the challenging real-time dense 3D surface reconstruction technologies are studied and reformulated for the reinvention of basic position-aware AR towards geometry-aware and the outlook of context- aware AR. We initially propose to reconstruct the dense environmental surface using the sparse point from Simultaneous Localisation and Map- ping (SLAM), but this approach is prone to fail in challenging Minimally Invasive Surgery (MIS) scenes such as the presence of deformation and surgical smoke. We subsequently adopt stereo vision with SLAM for more accurate and robust results. With the success of deep learning technology in recent years, we present learning based single image re- construction and achieve the state-of-the-art results. Moreover, we pro- posed context-aware AR, one step further from purely geometry-aware AR towards the high-level conceptual interaction modelling in complex AR environment for enhanced user experience. Finally, a learning-based smoke removal method is proposed to ensure an accurate and robust reconstruction under extreme conditions such as the presence of surgical smoke