ADVANCED MOTION MODELS FOR RIGID AND DEFORMABLE REGISTRATION IN IMAGE-GUIDED INTERVENTIONS

Image-guided surgery (IGS) has been a major area of interest in recent decades that continues to transform surgical interventions and enable safer, less invasive procedures. In the preoperative contexts, diagnostic imaging, including computed tomography (CT) and magnetic resonance (MR) imaging, offers a basis for surgical planning (e.g., definition of target, adjacent anatomy, and the surgical path or trajectory to the target). At the intraoperative stage, such preoperative images and the associated planning information are registered to intraoperative coordinates via a navigation system to enable visualization of (tracked) instrumentation relative to preoperative images. A major limitation to such an approach is that motions during surgery, either rigid motions of bones manipulated during orthopaedic surgery or brain soft-tissue deformation in neurosurgery, are not captured, diminishing the accuracy of navigation systems. This dissertation seeks to use intraoperative images (e.g., x-ray fluoroscopy and cone-beam CT) to provide more up-to-date anatomical context that properly reflects the state of the patient during interventions to improve the performance of IGS. Advanced motion models for inter-modality image registration are developed to improve the accuracy of both preoperative planning and intraoperative guidance for applications in orthopaedic pelvic trauma surgery and minimally invasive intracranial neurosurgery. Image registration algorithms are developed with increasing complexity of motion that can be accommodated (single-body rigid, multi-body rigid, and deformable) and increasing complexity of registration models (statistical models, physics-based models, and deep learning-based models). For orthopaedic pelvic trauma surgery, the dissertation includes work encompassing: (i) a series of statistical models to model shape and pose variations of one or more pelvic bones and an atlas of trajectory annotations; (ii) frameworks for automatic segmentation via registration of the statistical models to preoperative CT and planning of fixation trajectories and dislocation / fracture reduction; and (iii) 3D-2D guidance using intraoperative fluoroscopy. For intracranial neurosurgery, the dissertation includes three inter-modality deformable registrations using physic-based Demons and deep learning models for CT-guided and CBCT-guided procedures

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

Augmented Reality and Artificial Intelligence in Image-Guided and Robot-Assisted Interventions

In minimally invasive orthopedic procedures, the surgeon places wires, screws, and surgical implants through the muscles and bony structures under image guidance. These interventions require alignment of the pre- and intra-operative patient data, the intra-operative scanner, surgical instruments, and the patient. Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. State of the art approaches often support the surgeon by using external navigation systems or ill-conditioned image-based registration methods that both have certain drawbacks. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. Consequently, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions. This dissertation investigates the applications of AR, artificial intelligence, and robotics in interventional medicine. Our solutions were applied in a broad spectrum of problems for various tasks, namely improving imaging and acquisition, image computing and analytics for registration and image understanding, and enhancing the interventional visualization. The benefits of these approaches were also discovered in robot-assisted interventions. We revealed how exemplary workflows are redefined via AR by taking full advantage of head-mounted displays when entirely co-registered with the imaging systems and the environment at all times. The proposed AR landscape is enabled by co-localizing the users and the imaging devices via the operating room environment and exploiting all involved frustums to move spatial information between different bodies. The system's awareness of the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. We also leveraged the principles governing image formation and combined it with deep learning and RGBD sensing to fuse images and reconstruct interventional data. We hope that our holistic approaches towards improving the interface of surgery and enhancing the usability of interventional imaging, not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications

Archaeobotanical applications of microCT imaging

This thesis explores the ways in which the three-dimensional and non-destructive imaging technique of microCT can be applied to archaeobotanical materials to extract additional information previously inaccessible using traditional two-dimensional techniques. Across a series of eight publications, two microCT imaging protocols focusing on the imaging and analysis of two distinct types of archaeobotanical remains are presented along with archaeological case studies to which they have been successfully applied. Both protocols seek to utilise the relatively new imaging technique of microCT in order to explore the histories of some of the world's most important, yet in some cases understudied food crops including rice (Oryza sativa) in Island Southeast Asia, sorghum (Sorghum bicolor) and pearl millet (Pennisetum glaucum) in Africa, and taro (Colocasia esculenta), sweet potato (Ipomoea batatas), and yams (Dioscoreaceae) in Southeast Asia and the Pacific. The first protocol outlines how organic cereal tempers can be virtually extracted from inside pottery sherds through the use of microCT scanning and 3D digital segmentation techniques. These extracted digital remains can then be taxonomically identified and their domesticated status assessed using the morphological information only accessible with the penetrative X-rays of microCT. This protocol has been successfully applied to extract new rice and sorghum assemblages from previously excavated pottery sherds and their analysis has expanded our knowledge of the dispersal and early cultivation histories of these staple food crops. The second protocol uses microCT to build the first virtual reference collection of a greatly understudied type of archaeobotanical evidence, archaeological parenchyma. This protocol was developed by imaging samples of important root crops in the Southeast Asia and Pacific region from Jon Hather's parenchyma reference collection and applying his taxonomic identification method developed in the 1980s and 90s. Here his method is updated and adapted to include the added three-dimensional contextual information provided by microCT scanning as well as the greater range of anatomical variation captured both within and between species. The microCT datasets of these reference samples will form part of the first publicly accessible, online and virtual, archaeological parenchyma reference collection, which will hopefully encourage wider adoption and application of the technique. Both archaeobotanical microCT protocols presented here demonstrate the enormous potential of the technique to expand on our current sources of archaeobotanical evidence. The digital nature of the datasets presents the possibility of increasing analytical efficiency in the future with the development of automated archaeobotanical analyses

Recent Advances in Forensic Anthropological Methods and Research

Forensic anthropology, while still relatively in its infancy compared to other forensic science disciplines, adopts a wide array of methods from many disciplines for human skeletal identification in medico-legal and humanitarian contexts. The human skeleton is a dynamic tissue that can withstand the ravages of time given the right environment and may be the only remaining evidence left in a forensic case whether a week or decades old. Improved understanding of the intrinsic and extrinsic factors that modulate skeletal tissues allows researchers and practitioners to improve the accuracy and precision of identification methods ranging from establishing a biological profile such as estimating age-at-death, and population affinity, estimating time-since-death, using isotopes for geolocation of unidentified decedents, radiology for personal identification, histology to assess a live birth, to assessing traumatic injuries and so much more

An Exploration into the Relationship between Knee Shape and Kinematics Before and After Total Knee Replacement

The knee joint is unique in its design and it is thought that its articular shape is the main driver of biomechanical behaviour. Although the shape of the bony knee is acknowledged to change with osteoarthritis, the specific relationship between shape changes and function is not well understood. Deep flexion, specifically kneeling, is an ideal testing environment for the tibiofemoral joint because it is both a difficult and a desirable activity for people with knee osteoarthritis. Total knee replacement (TKR) is a surgery which attempts to restore the articular shape in order to enhance function. However, the influence of implant design on kneeling kinematics is unclear. This thesis examines the role of knee shape on kneeling kinematics before and following total knee replacement. The four aims of this thesis were to: 1) describe and quantify the main modes of shape variation which distinguish end-stage OA from age- and sex-similar healthy knees; 2) determine whether bony shape can predict deep kneeling kinematics in people with and without OA; 3) examine the published literature to determine whether there are any differences in contact patterns as a function of TKR design; and 4) to prospectively compare the six-degree-of-freedom kneeling kinematics of posterior-stabilised fixed bearing, cruciate-retaining fixed bearing and cruciate retaining rotating platform designs. Statistical shape modelling identified differences between osteoarthritic and healthy bony knee shape. Specifically: large expansions around the femoral cartilage plate; expansion and depression at the medial tibial border; and an area of corresponding bony expansion on the posterior aspect of the medial femur and tibia. Statistical shape modelling and image registration derived six degree of freedom kinematics were used to test for associations between knee shape and kneeling kinematics. The kinematic variability was described using bivariate principle component analysis. While we found weak associations between knee shape and kinematics, BMI and group (OA vs Healthy) also predicted kneeling kinematics. This indicates that factors other than bony shape are important in predicting kneeling kinematics. The third study was a systematic review with meta-analyses using quality effects models which characterised the influence of TKR implant design on kneeling contact patterns. The review found posterior stabilised designs were different to cruciate retaining designs, but the heterogeneity was high limiting any firm conclusions. The final study was a prospective randomised clinical trial examining the influence of TKR design on kneeling kinematics. The study found that posterior-stabilised fixed-bearing and cruciate-retaining rotating-platform designs had higher maximal flexion compared to cruciate retaining-fixed bearing designs. Furthermore, posterior-stabilised fixed-bearing femoral components were more posterior and the cruciate-retaining rotating-platform was in more external femoral rotation throughout flexion. However, there was substantial between-patient variability. This research breaks new ground around which aspects of bony shape are altered in osteoarthritis and how these shapes, and prosthetic design, influence kneeling kinematics. Furthermore, the methodologies employed in this thesis provide new ways of describing the variability in complex shape and kinematics datasets, which may contribute to the identification of therapeutic efficacy. Knee shape is considered to be an important driver for normal movement. However, the results of this thesis indicate that there are potentially other factors, including soft-tissue properties and patient-specific movement strategies, which might influence the kinematics of deep kneeling. The message for surgeons and other clinicians is that bony shape and TKR design are not the primary drivers of functional performance and that kneeling should be on their radar as an activity to which their patients should aspire