The diagnostic radiography curriculum and the process of its enactment are under researched in the United Kingdom. To date, there have been no published studies which have investigated the curriculum and the role of radiography educators from the multiple perspectives of radiography students, university radiography educators and clinical radiography educators, that is, a radiography education community. Accordingly, this study describes the perceptions and experiences of a radiography education community in relation to three research questions: 1. How does a radiography education community conceptualise the radiography knowledge and skills required of a diagnostic radiographer? 2. How does a radiography education community conceptualise the role played by university based and clinically based radiography educators in helping the radiography student acquire radiography knowledge and skills? 3. How does the community in this study compare with Lave and Wenger’s theoretical constructs of a situated learning, legitimate peripheral participation and Communities of Practice (CoP)? The epistemological foundation of the study is constructivism and the overarching methodology is a case study conducted within a single higher education institution and three of its associated clinical practice partner settings. The primary data collecting method comprised semi-structured interviews, supplemented by a critical review of germane literatures, government policy and the curriculum guidance provided by the relevant professional and statutory bodies. The theoretical framework in which the study is situated is based upon Lave and Wenger’s theories of situated learning, legitimate peripheral participation and communities of practice. The findings of the study reveal a radiography education community which is lacking any unifying pedagogic discourse. In particular, there is an absence of opportunities for cross-community working, especially in collaborative curriculum development and the process of its enactment. This is further compounded by the community’s narrow interpretation of what a curriculum should comprise. Currently there is a clear focus on knowledge content and curriculum as a product which fails to take into account praxis and the social context in which learning takes place. These findings have been summarised by a representation of the enacted curriculum as compared with the ‘ideological’ function of a radiography curriculum. Specific developments required of the curriculum include: (i) placing a greater emphasise on the vocational relevance of radiography knowledge; (ii) gaining a better understanding of tacit radiography knowledge; (iii) ensuring greater familiarity with the curriculum and (iv) enhancing the standard of clinical supervision. The radiography education community in this study evidences both convergence and divergence with Lave and Wenger’s theoretical constructs of situated learning, legitimate peripheral participation and community of practice. Within the context of radiography education the study also highlights the consequence of power relationships, the complexity of learning in and across multiple communities of practice and the importance of individual learner biographies, all of which are underdeveloped in Lave and Wenger’s theoretical discourse. These findings have been summarised in a proposed theoretical model for a radiography education community of practice. Three specific pedagogic and managerial inferences may be drawn from this study which will require staff development and consideration of how the diagnostic radiography programme is managed across the community. Firstly, context, process and praxis need to be carefully considered in the collaborative development, design and implementation of the curriculum. Secondly, the university and clinical educators need to reflect on their own learning and teaching skills by engaging more fully with pedagogy. Thirdly, communication across the radiography education community of practice must be improved.

Parenting capacity assessments (PCA) have been used in the child intervention system in Canada since at least the 1970s. They are used in other Western jurisdictions including the United Kingdom, Australia, New Zealand and the United States. There is a relatively large literature that considers the ways in which these assessments might be conducted. This thesis, drawing upon the prior work of the candidate, seeks to show that, despite widespread use, the PCA is a colonial methodology that should not be used with Indigenous peoples of Canada. The PCA draws upon Eurocentric understandings of parenting, definitions of minimal or good enough parenting, definitions of family and community as well as the use of methods that have neither been developed nor normed with Indigenous peoples. Using critical theory, particularly "Red Pedagogy" which is rooted in an Indigenous lens, the PCA is deconstructed to examine applicability to Indigenous populations of Canada, and potentially other populations that do not fit a Eurocentric understanding of family and parenting. Implications for clinical practice with Indigenous peoples are drawn which may have relevance for other populations.

This study aims to understand the use of a computer during GP consultations and to enable the development of EPR systems which are easier to review, enter data into, use to take action, and is more sensitive to the clinical context. This thesis reports the development of a multi-channel video and data capture toolkit, the ALFA (Activity Log File Aggregation) because existing observation techniques have limitations. None of the existing tools are designed to assess human-computer interaction in the context of the clinical consultation, where the social interaction is the prime focus. The ALFA tool-kit has been used to observe and study 163 live primary care consultations supported by computer systems with four different designs. A detailed analysis of consultation interactions was then performed focusing on doctor-patient communication and the integration of the computer into the consultation workflow. The data collection elements of the ALFA supported recording of consultation activities by providing rating techniques attuned with the characteristics of those interactions. The Log File Aggregation (LFA) component of the ALFA toolkit aggregated those multitudes of data files into a single navigable output that can be studied both quantitatively and qualitatively. A set of Unified Modelling Language (UML) sequence diagrams were then created as they could be used by software engineers to develop better systems. This research proposes a framework with three elements to analyse the computerised clinical consultation; (1) the overview of the context within which the consultation was carried out, (2) time taken to perform key consultation tasks and (3) the process used. Traditional analysis with its emphasis on the technology often misses crucial features of the complex work environments in which the technology is implemented. Direct observation could inform software designers in developing systems that are more readily integrated into clinical workflow. Direct observation of the consultation, using the ALFA toolkit is acceptable to patients; captures the context of the consultation the precise timing and duration of key tasks; and produces an output a software engineer can understand. ALFA offers a range of possibilities for research in the consulting room. The computer should be considered as an active element of the consultation; room layout and consultation models should let the computer in, while software engineers take in the capacity to sustain patient centred social interactions as a core facet of their design agenda.

Pulmonary embolism (PE) is an obstruction within the pulmonary arterial tree and in the majority of cases arises from a thrombosis that has travelled to the lungs via the venous system. Pulmonary embolism (PE) is a fatal condition which affects all age groups and is the third most common cause of death in the US. Computed tomographic angiography (CTA) imaging has recently emerged as an accurate method in the diagnosis of pulmonary embolism. Each CTA scan contains hundreds of CT images, so the accuracy and efficiency of interpreting such a large image data set is complicated due to various PE look-alikes and human factors such as attention span and eye fatigue. Moreover, manual reading and interpreting a large number of slices is time consuming and it is difficult to find all the pulmonary embolisms (PE) in a data set. Consequently, it is highly desirable to have a computer aided detection (CAD) system to assist radiologists in detecting and characterizing emboli in an accurate, efficient and reproducible manner. A computer aided detection (CAD) system for detection of pulmonary embolism is proposed in CTA images. Our approach is performed in three stages: firstly the pulmonary artery tree is extracted in the region of the lung and heart in order to reduce the search area (PE occurs inside the pulmonary artery) and aims to reduce the false detection rate. The pulmonary artery is separated from the surrounding organs by analyzing the second derivative of the Hessian matrix and then a hybrid method based on region growing and a new customized level set is used to extract the pulmonary artery (PA). In the level set implementation algorithm, a new stopping criterion is applied, a consideration often neglected in many level set implementations. In the second stage, pulmonary embolism candidates are detected inside the segmented pulmonary artery, by an analysis of three dimensional features inside the segmented artery. PE detection in the pulmonary artery is implemented using five detectors. Each detector responds to different properties of PE. In the third stage, filtering is used to exclude false positive detections associated with the partial volume effect on the artery boundary, flow void, lymphoid tissue, noise and motion artifacts. Soft tissue between the bronchial wall and the pulmonary artery is a common cause of false positive detection in CAD systems. A new feature, based on location is used to reduce false positives caused by soft tissue. The method was tested on 55 data scans (20 training data scans and 35 additional data scans for evaluation containing a total of 195 emboli). The system provided a segmentation of the PA up to the 6th division, which includes the sub-segmental level. Resulting performance gave 94% detection sensitivity with an average 4.1 false positive detections per scan. We demonstrated that the proposed CAD system can improve the performance of a radiologist, detecting 19 (11 %) extra PE which were not annotated by the radiologist.

Coronary artery disease is one of the most pernicious diseases around the world and early identification of vascular disease can help to reduce morbidity and mortality. Assessment of the degree of vascular obstruction, or stenosis, is critical for classifying the risks of the future vascular events. Automatic detection and quantification of stenosis are important in assessing coronary artery disease from medical imagery, especially for disease progression. Important factors affecting the reproducability and robustness of accuarate quantification arise from the partial volume effect and other noise sources. The main goal of this study is to present a fully automatic approach for detection and quantification of the stenosis in the coronary arteries. The proposed approach begins by building a 3D reconstruction of the coronary arterial system and then making accurate measurement of the vessel diameter from a robust estimate of the vessel cross-section. The proposed algorithm models the partial volume effect using a Markovian fuzzy clustering method in the process of accurate quantification of the degree of stenosis. To evaluate the accuracy and reproducibility of the measurement, the method was applied to a vascular phantom that was scanned using different protocols. The algorithm was applied to 20 CTA patient datasets containing a total of 85 stenoses, which were all successfully detected, with an average false positive rate of 0.7 per scan.

It is well known that the evolution of 4G-based mobile multimedia network systems will contribute significantly to future m-health applications that require high bandwidth and fast data rates. Central to the success of such emerging applications is the compatibility of broadband networks such as mobile WiMAX (IEEE 802.16e) and RSVP A, and especially their rate adaption issues combined with the acceptable real time medical quality of service requirements. The design of effective broadband mobile healthcare systems usmg emerging WiMAX and RSxP A networks is important from the medical perspective especially in applications such as remote medical ultrasound diagnostic systems. In this thesis, we introduce a new cross layer design approach for medical video streaming over mobile WiMAX and RSVP A networks. In particular, we propose an approach based on optimising medical Quality of Service (m-QoS) in mobile WiMAX network environments described in this work. Preliminary performance analysis of the proposed cross layer algorithm has been evaluated via simulation studies. These results show that the proposed cross layer optimizer achieves improved performance compatible with the necessary medical QoS requirements and constraints for the relevant clinical application. Furthermore, this work addresses the relevant challenges of cross layer design requirements for real time rate adaptation of ultrasound video streaming in Mobile WiMAX and RSVP A networks. The comparative performance analysis of such approach is validated in two experimental m-health testbed systems for both Mobile WiMAX and RSVP A networks. The experimental results show an improved performance of Mobile WiMAX compared to the RSVP A using the same cross layer optimisation approach. Additionally, we map the medical QoS to typical WiMAX QoS parameters in order to optimise the performance of these parameters in typical m-health scenarios. Preliminary performance analysis of the proposed multiparametric scenarios is evaluated to provide essential information for future medical QoS requirements and constraints.

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Hip fracture is the most common reason for admission to an orthopaedic trauma word. It is usually a 'Fragility' fracture caused by a fall affecting an older person with osteoporosis or osteopenia (a condition in which bones lose calcium and become thinner, but not as much as in osteoporosis). The National Hip Fracture Database worldwide reports the average age of a person with hip fracture is 84 years for men and 83 years for women, 76% of fracture occurs in women. By 2050, the worldwide incidence of hip fracture in men is projected to increase by 24% in women and 31% in men. Hip fractures due to sideways falls are a worldwide health problem, especially amongst elderly people. The experienced force to the proximal femur during a fall leading to hip fracture is significantly dependent on density, thickness and stiffness of the body during impact. The process of fracture and healing can only be understood in terms of structure and composition of the bone and also its mechanical properties. Bone fracture analysis investigates to predict various failure mechanisms under different loading conditions. In an effort to improve and assist scientists and researchers to predict the impact damage response of bone structures and estimate femoral fracture load in vitro, an accurate explicit finite element (14E) method has been investigated in this study. In the first part, the main goal is to create a 3D reconstruction and registration of semi-transparent Computed Tomography (CT) scan image data using SIMPLEWARE software. In the second part, effect of cortical thickness and impact velocity on the energy absorption of hip during a fall has been investigated on a 3D model. Additionally composite femora were mechanically tested to failure and regression analyses between measured fracture load and FE-predicted fracture load were performed. The results indicate that this sophisticated technique, which is still early in its development, can achieve precision comparable to that of densitometry and can predict femoral fracture load to within 18% with 95% confidence.