113 research outputs found

    Characterisation and State Estimation of Magnetic Soft Continuum Robots

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    Minimally invasive surgery has become more popular as it leads to less bleeding, scarring, pain, and shorter recovery time. However, this has come with counter-intuitive devices and steep surgeon learning curves. Magnetically actuated Soft Continuum Robots (SCR) have the potential to replace these devices, providing high dexterity together with the ability to conform to complex environments and safe human interactions without the cognitive burden for the clinician. Despite considerable progress in the past decade in their development, several challenges still plague SCR hindering their full realisation. This thesis aims at improving magnetically actuated SCR by addressing some of these challenges, such as material characterisation and modelling, and sensing feedback and localisation. Material characterisation for SCR is essential for understanding their behaviour and designing effective modelling and simulation strategies. In this work, the material properties of commonly employed materials in magnetically actuated SCR, such as elastic modulus, hyper-elastic model parameters, and magnetic moment were determined. Additionally, the effect these parameters have on modelling and simulating these devices was investigated. Due to the nature of magnetic actuation, localisation is of utmost importance to ensure accurate control and delivery of functionality. As such, two localisation strategies for magnetically actuated SCR were developed, one capable of estimating the full 6 degrees of freedom (DOFs) pose without any prior pose information, and another capable of accurately tracking the full 6-DOFs in real-time with positional errors lower than 4~mm. These will contribute to the development of autonomous navigation and closed-loop control of magnetically actuated SCR

    A novel optogenetics-based therapy for obstructive sleep apnoea

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    Obstructive sleep apnoea (OSA) is characterised by repeat upper airway narrowing and/or collapse during sleep. Many patients are sub-optimally treated due to poor tolerance or incomplete response to established therapies. We propose a novel, optogenetics-based therapy, that enables light-stimulation induced upper airway dilator muscle contractions to maintain airway patency. The primary aims of this thesis were to determine feasibility in a rodent model of OSA, and identify effective optogenetic constructs for activating upper airway muscles. Chapters 2 and 3 outline the development of a novel construct for the expression of light-sensitive proteins (opsins) in upper airway muscles, comparing two promotors and two recombinant adeno-associated virus capsids (rAAV) for optogenetic gene transfer. Results show that a muscle-specific promotor (tMCK) was superior to a non-specific promotor (CAG). With tMCK, opsin expression in the tongue was 470% greater (p=0.013, RM-ANOVA), brainstem expression was abolished, and light stimulation facilitated a 66% increase in muscle activity from that recorded during unstimulated breaths in an acute model of OSA (p<0.001, linear mixed model) (Chapter 2). Moreover, a novel, highly myotropic rAAV serotype, AAVMYO, was superior to a wild-type serotype, AAV9. The AAVMYO serotype driven by tMCK facilitated a further increase in muscle activity with light stimulation to 194% of that recorded during unstimulated breaths (p<0.001, linear mixed model) (Chapter 3). Finally, ultrasound imaging confirmed that the optimised construct was able to generate effective light-induced muscle contractions and airway dilation (Chapter 4). A secondary aim was to advance preclinical trials for the proposed therapy. To this end, a surgical protocol for chronic implantation of light delivery hardware and recording electrodes in rodents was developed (Chapter 5). The final protocol will allow us to determine the effects of acute and chronic light stimulation on opsin-expressing upper airway muscles during natural sleep. In summary, Chapters 2 to 4 provide proof-of-concept for a non-invasive optogenetics-based OSA therapy. The combination of a muscle-specific promotor and a muscle-specific viral vector presents a novel and highly effective method of inducing light sensitivity into skeletal muscle and facilitating light-evoked airway dilation. Finally, Chapter 5 commences the development of a surgical protocol that will aid ongoing preclinical trials

    3 Dimensional Dense Reconstruction: A Review of Algorithms and Dataset

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    3D dense reconstruction refers to the process of obtaining the complete shape and texture features of 3D objects from 2D planar images. 3D reconstruction is an important and extensively studied problem, but it is far from being solved. This work systematically introduces classical methods of 3D dense reconstruction based on geometric and optical models, as well as methods based on deep learning. It also introduces datasets for deep learning and the performance and advantages and disadvantages demonstrated by deep learning methods on these datasets.Comment: 16 page

    Tracking and Mapping in Medical Computer Vision: A Review

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    As computer vision algorithms are becoming more capable, their applications in clinical systems will become more pervasive. These applications include diagnostics such as colonoscopy and bronchoscopy, guiding biopsies and minimally invasive interventions and surgery, automating instrument motion and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing and applying algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision. We begin with describing our review process, which results in a final list of 515 papers that we cover. We then give a high-level summary of the state of the art and provide relevant background for those who need tracking and mapping for their clinical applications. We then review datasets provided in the field and the clinical needs therein. Then, we delve in depth into the algorithmic side, and summarize recent developments, which should be especially useful for algorithm designers and to those looking to understand the capability of off-the-shelf methods. We focus on algorithms for deformable environments while also reviewing the essential building blocks in rigid tracking and mapping since there is a large amount of crossover in methods. Finally, we discuss the current state of the tracking and mapping methods along with needs for future algorithms, needs for quantification, and the viability of clinical applications in the field. We conclude that new methods need to be designed or combined to support clinical applications in deformable environments, and more focus needs to be put into collecting datasets for training and evaluation.Comment: 31 pages, 17 figure

    Investigating Ultrasound-Guided Autonomous Assistance during Robotic Minimally Invasive Surgery

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    Despite it being over twenty years since the first introduction of robotic surgical systems in common surgical practice, they are still far from widespread across all healthcare systems, surgical disciplines and procedures. At the same time, the systems that are used act as mere tele-manipulators with motion scaling and have yet to make use of the immense potential of their sensory data in providing autonomous assistance during surgery or perform tasks themselves in a semi-autonomous fashion. Equivalently, the potential of using intracorporeal imaging, particularly Ultrasound (US) during surgery for improved tumour localisation remains largely unused. Aside from the cost factors, this also has to do with the necessity of adequate training for scan interpretation and the difficulty of handling an US probe near the surgical sight. Additionally, the potential for automation that is being explored in extracorporeal US using serial manipulators does not yet translate into ultrasound-enabled autonomous assistance in a surgical robotic setting. Motivated by this research gap, this work explores means to enable autonomous intracorporeal ultrasound in a surgical robotic setting. Based around the the da Vinci Research Kit (dVRK), it first develops a surgical robotics platform that allows for precise evaluation of the robot’s performance using Infrared (IR) tracking technology. Based on this initial work, it then explores the possibility to provide autonomous ultrasound guidance during surgery. Therefore, it develops and assesses means to improve kinematic accuracy despite manipulator backlash as well as enabling adequate probe position with respect to the tissue surface and anatomy. Founded on the acquired anatomical information, this thesis explores the integration of a second robotic arm and its usage for autonomous assistance. Starting with an autonomously acquired tumor scan, the setup is extended and methods devised to enable the autonomous marking of margined tumor boundaries on the tissue surface both in a phantom as well as in an ex-vivo experiment on porcine liver. Moving towards increased autonomy, a novel minimally invasive High Intensity Focused Ultrasound (HIFUS) transducer is integrated into the robotic setup including a sensorised, water-filled membrane for sensing interaction forces with the tissue surface. For this purpose an extensive material characterisation is caried out, exploring different surface material pairings. Finally, the proposed system, including trajectory planning and a hybrid-force position control scheme are evaluated in a benchtop ultrasound phantom trial

    Design of PEIS: A Low-Cost Pipe Inspector Robot

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    This paper outlines the design of a novel mechatronic system for semi-automatic in-spection and white-water in-pipe obstruction removals without the need for destructive methods or specialized manpower. The device is characterized by a lightweight structure and high trans-portability. It is composed by a front, a rear and a central module that realize the worm-like lo-comotion of the robot with a specifically designed driving mechanism for the straight motion of the robot along the pipeline. The proposed mechatronic system is easily adaptable to pipes of various sizes. Each module is equipped with a motor that actuates three slider-crank-based mechanisms. The central module incorporates a length-varying mechanism that allows forward and backward locomotion. The device is equipped with specific low-cost sensors that allow an operator to monitor the device and locate an obstruction in real time. The movement of the device can be automatic or controlled manually by using a specific user-friendly control board and a laptop. Preliminary laboratory tests are reported to demonstrate the engineering feasibility and effectiveness of the proposed design, which is currently under patenting

    Advances in Minimally Invasive Surgery

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    The minimally invasive approach in medicine is one of the most common areas of interest in surgery.Advances in Minimally Invasive Surgery describes the latest trends, indications, techniques, and approaches in minimally invasive surgery. It provides step-by-step instructions for both routine and diagnostic procedures via illustrations and video collection

    Deep Causal Learning for Robotic Intelligence

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    This invited review discusses causal learning in the context of robotic intelligence. The paper introduced the psychological findings on causal learning in human cognition, then it introduced the traditional statistical solutions on causal discovery and causal inference. The paper reviewed recent deep causal learning algorithms with a focus on their architectures and the benefits of using deep nets and discussed the gap between deep causal learning and the needs of robotic intelligence
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