195 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

    Image-guided prostate biopsy robots: A review

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    At present, the incidence of prostate cancer (PCa) in men is increasing year by year. So, the early diagnosis of PCa is of great significance. Transrectal ultrasonography (TRUS)-guided biopsy is a common method for diagnosing PCa. The biopsy process is performed manually by urologists but the diagnostic rate is only 20%–30% and its reliability and accuracy can no longer meet clinical needs. The image-guided prostate biopsy robot has the advantages of a high degree of automation, does not rely on the skills and experience of operators, reduces the work intensity and operation time of urologists and so on. Capable of delivering biopsy needles to pre-defined biopsy locations with minimal needle placement errors, it makes up for the shortcomings of traditional free-hand biopsy and improves the reliability and accuracy of biopsy. The integration of medical imaging technology and the robotic system is an important means for accurate tumor location, biopsy puncture path planning and visualization. This paper mainly reviews image-guided prostate biopsy robots. According to the existing literature, guidance modalities are divided into magnetic resonance imaging (MRI), ultrasound (US) and fusion image. First, the robot structure research by different guided methods is the main line and the actuators and material research of these guided modalities is the auxiliary line to introduce and compare. Second, the robot image-guided localization technology is discussed. Finally, the image-guided prostate biopsy robot is summarized and suggestions for future development are provided

    Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

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    Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

    Development and Validation of Mechatronic Systems for Image-Guided Needle Interventions and Point-of-Care Breast Cancer Screening with Ultrasound (2D and 3D) and Positron Emission Mammography

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    The successful intervention of breast cancer relies on effective early detection and definitive diagnosis. While conventional screening mammography has substantially reduced breast cancer-related mortalities, substantial challenges persist in women with dense breasts. Additionally, complex interrelated risk factors and healthcare disparities contribute to breast cancer-related inequities, which restrict accessibility, impose cost constraints, and reduce inclusivity to high-quality healthcare. These limitations predominantly stem from the inadequate sensitivity and clinical utility of currently available approaches in increased-risk populations, including those with dense breasts, underserved and vulnerable populations. This PhD dissertation aims to describe the development and validation of alternative, cost-effective, robust, and high-resolution systems for point-of-care (POC) breast cancer screening and image-guided needle interventions. Specifically, 2D and 3D ultrasound (US) and positron emission mammography (PEM) were employed to improve detection, independent of breast density, in conjunction with mechatronic and automated approaches for accurate image acquisition and precise interventional workflow. First, a mechatronic guidance system for US-guided biopsy under high-resolution PEM localization was developed to improve spatial sampling of early-stage breast cancers. Validation and phantom studies showed accurate needle positioning and 3D spatial sampling under simulated PEM localization. Subsequently, a whole-breast spatially-tracked 3DUS system for point-of-care screening was developed, optimized, and validated within a clinically-relevant workspace and healthy volunteer studies. To improve robust image acquisition and adaptability to diverse patient populations, an alternative, cost-effective, portable, and patient-dedicated 3D automated breast (AB) US system for point-of-care screening was developed. Validation showed accurate geometric reconstruction, feasible clinical workflow, and proof-of-concept utility across healthy volunteers and acquisition conditions. Lastly, an orthogonal acquisition and 3D complementary breast (CB) US generation approach were described and experimentally validated to improve spatial resolution uniformity by recovering poor out-of-plane resolution. These systems developed and described throughout this dissertation show promise as alternative, cost-effective, robust, and high-resolution approaches for improving early detection and definitive diagnosis. Consequently, these contributions may advance breast cancer-related equities and improve outcomes in increased-risk populations and limited-resource settings

    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

    Novel Magnetic Resonance Imaging-Compatible Mechatronic Needle Guidance System for Prostate Focal Laser Ablation Therapy

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    Advances in prostate cancer (PCa) screening techniques have led to diagnosis of many cases of low-grade and highly localized disease. Conventional whole-gland therapies often result in overtreatment in such cases and debate still surrounds the optimal method of oncologic control. MRI-guided prostate focal laser ablation (FLA) is a minimally invasive treatment option, which has demonstrated potential to destroy localized lesions while sparing healthy prostatic tissue, thereby reducing treatment-related side effects. Many challenges still exist in the development of FLA, including patient selection; tumour localization, visualization, and characterization; needle guidance; and evaluation of treatment efficacy. The objective of this thesis work was to advance and enhance techniques for needle guidance in MRI-guided focal laser ablation (FLA) therapy of PCa. Several steps were taken in achieving this goal. Firstly, we evaluated the overlap between identified lesions and MRI-confirmed ablation regions using conventional needle guidance. Non-rigid thin-plate spline registration of pre-operative and intra-operative images was performed to align lesions with ablation boundaries and quantify the degree of coverage. Complete coverage of the lesion with the ablation zone is a clinically important metric of success for FLA therapy and we found it was not achieved in many cases. Therefore, our next step was to develop an MRI-compatible, remotely actuated mechatronic system for transperineal FLA of prostate cancer. The system allows physicians in the MRI scanner control room to accurately target lesions through 4 degrees of freedom while the patient remains in the scanner bore. To maintain compatibility with the MRI environment, piezoelectric motors were used to actuate the needle guidance templates, the device was constructed from non-ferromagnetic materials, and all cables were shielded from electromagnetic interference. The MR compatibility and needle placement accuracy of the device were evaluated with virtual and phantom targets. The system should next be validated for accuracy and usefulness in a clinical trial where more complex tissue properties and potential patient motion will be encountered. Future advances in modeling the tissue properties and compensating for deformation of the prostate, as well as predicting needle deflection, will further bolster the potential of FLA as option for the management of PCa

    Technology, Science and Culture: A Global Vision, Volume IV

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