Quantitative Analysis of Three-Dimensional Cone-Beam Computed Tomography Using Image Quality Phantoms

In the clinical setting, weight-bearing static 2D radiographic imaging and supine 3D radiographic imaging modalities are used to evaluate radiographic changes such as, joint space narrowing, subchondral sclerosis, and osteophyte formation. These respective imaging modalities cannot distinguish between tissues with similar densities (2D imaging), and do not accurately represent functional joint loading (supine 3D imaging). Recent advances in cone-beam CT (CBCT) have allowed for scanner designs that can obtain weight-bearing 3D volumetric scans. The purpose of this thesis was to analyze, design, and implement advanced imaging techniques to quantify image quality parameters of reconstructed image volumes generated by a commercially-available CBCT scanner, and a novel ceiling-mounted CBCT scanner. In addition, imperfections during rotation of the novel ceiling-mounted CBCT scanner were characterized using a 3D printed calibration object with a modification to the single marker bead method, and prospective geometric calibration matrices

Computer-aided diagnosis of complications of total hip replacement X-ray images

Hip replacement surgery has experienced a dramatic evolution in recent years supported by the latest developments in many areas of technology and surgical procedures. Unfortunately complications that follow hip replacement surgery remains the most challenging dilemma faced both by the patients and medical experts. The thesis presents a novel approach to segment the prosthesis of a THR surgical process by using an Active Contour Model (ACM) that is initiated via an automatically detected seed point within the enarthrosis region of the prosthesis. The circular area is detected via the use of a Fast, Randomized Circle Detection Algorithm. Experimental results are provided to compare the performance of the proposed ACM based approach to popular thresholding based approaches. Further an approach to automatically detect the Obturator Foramen using an ACM approach is also presented. Based on analysis of how medical experts carry out the detection of loosening and subsidence of a prosthesis and the presence of infections around the prosthesis area, this thesis presents novel computational analysis concepts to identify the key feature points of the prosthesis that are required to detect all of the above three types of complications. Initially key points along the prosthesis boundary are determined by measuring the curvature on the surface of the prosthesis. By traversing the edge pixels, starting from one end of the boundary of a detected prosthesis, the curvature values are determined and effectively used to determine key points of the prosthesis surface and their relative positioning. After the key-points are detected, pixel value gradients across the boundary of the prosthesis are determined along the boundary of the prosthesis to determine the presence of subsidence, loosening and infections. Experimental results and analysis are presented to show that the presence of subsidence is determined by the identification of dark pixels around the convex bend closest to the stem area of the prosthesis and away from it. The presence of loosening is determined by the additional presence of dark regions just outside the two straight line edges of the stem area of the prosthesis. The presence of infections is represented by the determination of dark areas around the tip of the stem of the prosthesis. All three complications are thus determined by a single process where the detailed analysis defer. The experimental results presented show the effectiveness of all proposed approaches which are also compared and validated against the ground truth recorded manually with expert user input

Image Processing Algorithms for Detection of Anomalies in Orthopedic Surgery Implants

Orthopedic implant procedures for hip implants are performed on 300,000 patients annually in the United States, with 22.3 million procedures worldwide. While most such operations are successfully performed to relieve pain and restore joint function for the duration of the patient\u27s life, advances in medicine have enabled patients to outlive the life of their implant, increasing the likelihood of implant failure. There is significant advantage to the patient, the surgeon, and the medical community in early detection of implant failures.The research work presented in this thesis demonstrates a non-invasive digital image processing technique for the automated detection of specific arthroplasty failures before requiring revision surgery. This thesis studies hip implant loosening as the primary cause of failure. A combination of digital image segmentation, representation and numerical description is employed and validated on 2-D X-ray images of hip implant phantoms to detect 3-D rotations of the implant, with the support of radial basis function neural networks to accomplish this task. A successful clinical implementation of the methods developed in this thesis can eliminate the need for revision surgery and prolong the life of the orthopedic implant

Development and Experimental Analysis of Wireless High Accuracy Ultra-Wideband Localization Systems for Indoor Medical Applications

This dissertation addresses several interesting and relevant problems in the field of wireless technologies applied to medical applications and specifically problems related to ultra-wideband high accuracy localization for use in the operating room. This research is cross disciplinary in nature and fundamentally builds upon microwave engineering, software engineering, systems engineering, and biomedical engineering. A good portion of this work has been published in peer reviewed microwave engineering and biomedical engineering conferences and journals. Wireless technologies in medicine are discussed with focus on ultra-wideband positioning in orthopedic surgical navigation. Characterization of the operating room as a medium for ultra-wideband signal transmission helps define system design requirements. A discussion of the first generation positioning system provides a context for understanding the overall system architecture of the second generation ultra-wideband positioning system outlined in this dissertation. A system-level simulation framework provides a method for rapid prototyping of ultra-wideband positioning systems which takes into account all facets of the system (analog, digital, channel, experimental setup). This provides a robust framework for optimizing overall system design in realistic propagation environments. A practical approach is taken to outline the development of the second generation ultra-wideband positioning system which includes an integrated tag design and real-time dynamic tracking of multiple tags. The tag and receiver designs are outlined as well as receiver-side digital signal processing, system-level design support for multi-tag tracking, and potential error sources observed in dynamic experiments including phase center error, clock jitter and drift, and geometric position dilution of precision. An experimental analysis of the multi-tag positioning system provides insight into overall system performance including the main sources of error. A five base station experiment shows the potential of redundant base stations in improving overall dynamic accuracy. Finally, the system performance in low signal-to-noise ratio and non-line-of-sight environments is analyzed by focusing on receiver-side digitally-implemented ranging algorithms including leading-edge detection and peak detection. These technologies are aimed at use in next-generation medical systems with many applications including surgical navigation, wireless telemetry, medical asset tracking, and in vivo wireless sensors

Hand X-ray absorptiometry for measurement of bone mineral density on a slot-scanning X-ray imaging system

Includes bibliographical references.Bone mineral density (BMD) is an indicator of bone strength. While femoral and spinal BMDs are traditionally used in the management of osteoporosis, BMD at peripheral sites such as the hand has been shown to be useful in evaluating fracture risk for axial sites. These peripheral locations have been suggested as alternatives to the traditional sites for BMD measurement. Dual-energy X-ray absorptiometry (DXA) is the gold standard for measuring BMD due to low radiation dose, high accuracy and proven ability to evaluate fracture risk. Computed digital absorptiometry (CDA) has also been shown to be very effective at measuring the bone mass in hand bones using an aluminium step wedge as a calibration reference. In this project, the aim was to develop algorithm s for accurate measurement of BMD in hand bones on a slot - scanning digital radiography system. The project assess e d the feasibility of measuring bone mineral mass in hand bones using CDA on the current system. Images for CDA - based measurement were acquired using the default settings on the system for a medium sized patient. A method for automatic processing of the hand images to detect the aluminium step wedge, included in the scan for calibration, was developed and the calibration accuracy of the step wedge was evaluated. The CDA method was used for computation of bone mass with units of equivalent aluminium thickness (mmA1). The precision of the method was determined by taking three measurements in each of 1 6 volunteering subjects and computing the root - mean - square coefficient of variation (CV) of the measurements. The utility of the method was assessed by taking measurements of excised bones and assessing the correlation between the measured bone mass and ash weight obtained by incinerating the bones. The project also assessed the feasibility of implementing a DXA technique using two detectors in a slot-scanning digital radiography system to acquire dual-energy X-ray images for measuring areal and volumetric BMD of the middle phalanx of the middle finger. The dual-energy images were captured in two consecutive scans. The first scan captured the low- energy image using the detector in its normal set-up. The second scan captured the high- energy image with the detector modified to include an additional scintillator to simulate the presence of a second detector that would capture the low-energy image in a two-detector system. Scan parameters for acquisition of the dual-energy images were chosen to optimise spectral separation, entrance dose and image quality. Simulations were carried out to evaluate the spectral separation of the low- and high-energy spectra

Applied AI/ML for automatic customisation of medical implants

Most knee replacement surgeries are performed using ‘off-the-shelf’ implants, supplied with a set number of standardised sizes. X-rays are taken during pre-operative assessment and used by clinicians to estimate the best options for patients. Manual templating and implant size selection have, however, been shown to be inaccurate, and frequently the generically shaped products do not adequately fit patients’ unique anatomies. Furthermore, off-the-shelf implants are typically made from solid metal and do not exhibit mechanical properties like the native bone. Consequently, the combination of these factors often leads to poor outcomes for patients. Various solutions have been outlined in the literature for customising the size, shape, and stiffness of implants for the specific needs of individuals. Such designs can be fabricated via additive manufacturing which enables bespoke and intricate geometries to be produced in biocompatible materials. Despite this, all customisation solutions identified required some level of manual input to segment image files, identify anatomical features, and/or drive design software. These tasks are time consuming, expensive, and require trained resource. Almost all currently available solutions also require CT imaging, which adds further expense, incurs high levels of potentially harmful radiation, and is not as commonly accessible as X-ray imaging. This thesis explores how various levels of knee replacement customisation can be completed automatically by applying artificial intelligence, machine learning and statistical methods. The principal output is a software application, believed to be the first true ‘mass-customisation’ solution. The software is compatible with both 2D X-ray and 3D CT data and enables fully automatic and accurate implant size prediction, shape customisation and stiffness matching. It is therefore seen to address the key limitations associated with current implant customisation solutions and will hopefully enable the benefits of customisation to be more widely accessible.Open Acces

3D Elbow Kinematics with Monoplanar Fluoroscopy: In Silico Evaluation

An in-silico assessment of the performance of 3D video-fluoroscopy for the analysis of the kinematics of long bones is proposed. A reliable knowledge of in-vivo joints kinematics in physiological conditions is fundamental in the clinical field. 3D video-fluoroscopy theoretically permits a mm/deg level of accuracy in joint motion analysis, but the optimization algorithm for the pose estimation is highly dependent on the geometry of the bone segment analyzed. An automated technique based on distance maps and tangency condition was applied to the elbow bones. The convergence domain was explored to quantify and optimize measurement accuracy in terms of bias and precision. By conditioning the optimization algorithm using simple image features, the estimation error had small dispersion (interquartile range within 0.5 and 0.025 mm/deg for out-of-plane and in-plane pose parameters, resp.), but with occasional bias and outliers. 3D video-fluoroscopy produced promising results for the elbow joint, but further in-vitro validation studies should be carried out

Development and Validation of a Markerless Radiostereometric Analysis (RSA)System

A markerless radiostereometric analysis (RSA) system was developed to measure three- dimensional (3D) skeletal kinematics using biplanar fluoroscopy. A virtual set-up was created, in which the fluoroscope foci and image planes were positioned. Computed tomography (CT) was used to create 3D bone models that were imported into the virtual set-up and manually moved until their projections, as viewed from the two foci, matched the two images. The accuracy of the markerless RSA system in determining relative shoulder kinematic translations and orientations was evaluated against the “gold standards” of a precisions cross-slide table and a standard RSA system, respectively. Average root mean squared errors (RMSEs) of 0.082 mm and 1.18° were found. In an effort to decrease subject’s radiation exposure, the effect of lowering CT dosage on markerless RSA accuracy was evaluated. Acceptable accuracies were obtained using bone models derived from one-ninth of the normal radiation dose