Yes / Skill mix has been established as one method of maintaining imaging service delivery, with vertical and horizontal substitution of roles and tasks. Assistant practitioners (APs) have been undertaking limited imaging practice for almost two decades, but there remains a paucity of evidence related to the impact of their roles. Methods: This article reports on an electronic survey of individual APs within the NHS in the UK to explore utilisation, role scope and aspirations. Results: Responses were analysed from APs (n = 193) employed in 97 different organisations across the UK. The majority work in general radiography or mammography, with very few responses from other imaging modalities. Training routes varied across modalities, with most achieving Band 4 under Agenda for Change on completion of education. Limitations on practice vary between organisations and modalities, with many reporting blurring of the radiographer-AP boundary. Many aspire to continue their training to achieve registrant radiographer status, although there were clear frustrations from respondents over the lack of overt career prospects. Conclusion: Integration of the role into imaging department practice does not appear to be universal or consistent and further research is required to examine the optimal skill mix composition. Advances in knowledge: Skill mix implementation is inconsistent across modalities and geography in the UK. Opportunities for further workforce utilisation and expansion are evident.

Yes / The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radiographer role is lacking. This paper discusses the potential impact of artificial intelligence (AI) on the radiography profession by assessing current workflow and cross-mapping potential areas of AI automation such as procedure planning, image acquisition and processing. We also highlight the opportunities that AI brings including enhancing patient-facing care, increased cross-modality education and working, increased technological expertise and expansion of radiographer responsibility into AI-supported image reporting and auditing roles.

Yes / Introduction: In the UK the development of skill mix in radiography at the end of the 20th century formalised the assistant practitioner role, separating it from the support worker function. The key aim was to increase imaging capacity whilst enabling opportunities for career progression within both the support and radiography workforce. There has been limited examination of these support and assistive roles and this review aims to explore the current evidence. Methods: This scoping review used a systematic search strategy and interrogated MEDLINE, CINAHL, Scopus and Google Scholar. Primary research articles published in the English-language referring to studies conducted in the UK on assistant or support roles in radiography were sought. The sourced data was uploaded to a web-based review platform for screening. Results: The literature search identified only 11 articles which met the search criteria, of which only one referred to the support worker role. Adopting a primarily qualitative approach the quality of the articles varied. Thematic analysis was undertaken using a priori themes role purpose, outcomes, aspirations and capacity building. Conclusion: There is limited research evidence of capacity generation with most presenting individual perspectives. Job satisfaction and career aspirations within the support and assistive workforce are evident but there is still confusion over scope of practice and supervision. Implications for practice: The support and assistive workforce are a key part of the diagnostic imaging workforce but limited research evidence examining these roles has been published. Further research exploring the impact of skill mix changes across all levels and imaging professions is required. / The study was funded by the NIHR Health and Social Care Delivery Research programme (I.D. NIHR133813).

Tsang, Man Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 57-60). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese.

Although the current OCT imaging system was designed to examine the retinal structures, a novel application in imaging the anterior chamber angle was studied in section 3.7. OCT was demonstrated to be clinically useful for visualization of the different patterns of angle configurations in different forms of angle closure glaucoma. / In section 3.5, RNFL measurement by OCT was cross-validated by another nerve fiber analyzer, scanning laser polarimetry (SLP). While both OCT and SLP demonstrated comparable diagnostic performance for glaucoma detection and high correlation in the respective RNFL measurements, OCT was found to provide a closer estimation of RNFL thickness with reference to the reported histological measurements. In section 3.6, the structural-functional relationship between RNFL thickness and visual sensitivity was evaluated and compared between OCT and SLP. The relationships were found to be dependent on the choice of the perimetry scale, the type of RNFL measuring devices and the characteristics of the studied subjects. It was concluded that regression analysis of the structural-functional profile could provide important information in the assessment of the trend and pattern of glaucoma progression. / In summary, optical coherence tomography was shown to be useful in the diagnosis of glaucoma and in the evaluation of the trend and pattern of disease progression. / Objectives. The research project was designed to investigate the applications of optical coherence tomography in the assessment of glaucoma. The goals are to identify sensitive and specific anatomic markers, and analytical method for detection of glaucomatous changes, to evaluate the intricate structural-functional relationships in glaucoma with regression analysis and to assess the potential application of optical coherence tomography imaging system in visualization of the anterior chamber angle with a view to obtain OCT data to help understanding the pathophysiology of different forms of angle-closure glaucoma. / Sections 3.1 to 3.3 were designed to identify the most sensitive and specific diagnostic marker(s) for glaucoma detection. Peripapillary retinal nerve fiber layer (RNFL), macular thickness, optic nerve head parameters measured with different reference planes, and a novel anatomic marker - macular nerve fiber layer were investigated. The averaged peripapillary RNFL thickness measured with a high resolution scan (512 scan point) was found to have the best discriminating power for detection of glaucoma. It also has the strongest correlation with visual function. To examine if utilization of the complete data profile of peripapillary RNFL could further improve diagnostic sensitivity, a novel approach with the use of neural network trained to recognize RNFL pattern was studied in section 3.4. It was concluded that neural network analysis could enhance the diagnostic performance for glaucoma detection. / Summary. Glaucoma is a progressive optic neuropathy characterized by the loss of retinal ganglion cells resulting in constriction of visual field and loss of vision as the disease progresses. Since structural damage in glaucoma occurs well before any detectable loss in visual function, clinical examination of the optic nerve head and its nerve fiber layer is crucial in establishing the diagnosis, monitoring the progression and initiating treatment before irreversible damage takes place. The present research project is composed of 7 coherent studies (sections 3.1 to 3.7), aiming to investigate the clinical applications of optical coherence tomography (OCT), an advanced imaging device for detailed examination of optic nerve head and nerve fiber layer, in the assessment of glaucoma. / Leung Kai-shun. / "June 2006." / Adviser: Chi Pui Pang. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6323. / Thesis (M.D.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (p. 212-227). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / School code: 1307.

[Truncated abstract] Hypothesis: There is deficiency in the evidence base and scientific underpinning of existing diagnostic imaging pathways (DIP) for diagnostic endpoints. Objective: a) To carry out systematic review of literature in relation to use of diagnostic imaging tests for diagnosis and investigation of 78 common clinical problems, b) To identify deficiencies and controversies in existing diagnostic imaging pathways, and to develop a new set of consensus based pathways for diagnostic imaging (DIP) supported by evidence as an education and decision support tool for hospital based doctors and general practitioners, c) To carry out a trial dissemination, implementation and evaluation of DIP. Methods: 78 common clinical presentations were chosen for development of DIP. For general practitioners, clinical topics were selected based on the following criteria: common clinical problem, complex in regards to options available for imaging, subject to inappropriate imaging resulting in unnecessary expenditure and /or radiation exposure, and new options for imaging of which general practitioners may not be aware. For hospital based junior doctors and medical students, additional criteria included: acute presentation when immediate access to expert radiological opinion may be lacking and clinical problem for which there is a need for education. Systematic review of the literature in relation to each of the 78 topics was carried out using Ovid, Pubmed and Cochrane Database of Systematic Reviews. ... The electronic environment and the method of delivery provided a satisfactory medium for dissemination. Getting DIP implemented required vigorous effort. Knowledge of diagnostic imaging and requesting behaviour tended to become more aligned with DIP following a period of intensive marketing. Conclusions: Systematic review of literature and input and feedback from various clinicians and radiologists led to the development of 78 consensus based Diagnostic Imaging Pathways supported by evidence. These pathways are a valuable decision support tool and are a definite step towards incorporating evidence based medicine in patient management. The clinical and academic content of DIP is of practical use to a wide range of clinicians in hospital and general practice settings. It is source of high level knowledge; a reference tool for the latest available and most effective imaging test for a particular clinical problem. In addition, it is an educational tool for medical students, junior doctors, medical imaging technologists, and allied health care personnel.

無線膠囊內窺鏡（CE）是一種用於檢查整個胃腸道，尤其是小腸的無創技術。它極大地改善了許多小腸疾病的診斷和管理方式，如不明原因的消化道出血，克羅恩病，小腸腫瘤，息肉綜合征等。儘管膠囊內窺鏡有很好的臨床表現，但它仍然有一定的局限性。主要問題是每次檢查產生約50,000 幅低質量的圖像，對於醫生來說，評估如此大量的圖像是一項非常耗時、耗力的工作。 / 到目前為止，對於膠囊內窺鏡的分析和評估，學者們都把膠囊內窺鏡圖像視為單獨的，獨立的觀測對象。事實並非如此，因為圖像之間往往有顯著的重疊。特別是當膠囊內窺鏡在被小腸蠕動緩緩推動時，它可以捕捉同一病灶的多個視圖。我們的研究目的是使用所有可用的資訊，包括多幅圖像，研究對於膠囊內窺鏡的電腦輔助診斷（CAD）系統。 / 在這篇論文中，我們提出了一個嵌入分類器的多類隱馬爾可夫模型（HMM）的方案，它可以融合多幅相鄰圖像的時間資訊。由於膠囊內窺鏡圖像的品質比較低，我們首先進行預處理，以加強膠囊內窺鏡圖像，增加其對比度，消除噪聲。我們調查研究了多種圖像增強的方法，並調整了它們的參數使其適用於膠囊內窺鏡圖像。 / 對於基於單幅圖像的有監督的分類，AdaBoost 作為一個集成分類器來融合多個分類器，即本論文中的支持向量機（SVM），k-近鄰（k-NN），貝葉斯分類。在分類之前，我們提取和融合了顏色，邊緣和紋理特徵。 / 對於無線膠囊內窺鏡的視頻摘要，我們提出了有監督和無監督的兩類方法。對於有監督方法，我們提出了一個基於隱馬爾可夫模型的，靈活的，可擴展的框架，用於整合膠囊內窺鏡中連續圖像的時間資訊。它可以擴展到多類別，多特徵，多狀態。我們還提出了聯合隱馬爾可夫模型和並行隱馬爾可夫（PHMM）模型對系統進行改進，它們可以被看作是決策級的資訊融合。聯合隱馬爾可夫模型通過多層次的隱馬爾可夫模型，結合不同的資訊來源，對膠囊內窺鏡視頻進行分類和視頻摘要。 並行隱馬爾可夫模型採用貝葉斯推理，在決策時融合多個不同來源的資訊。對於無監督的方法，我們首先提出了一種基於顏色的特徵提取方法。在反色顏色空間中對亮度不變的色度不變矩用來表示膠囊內窺鏡圖像的顏色特徵。接著，我們又提出了一種基於輪廓元（Contourlet）變換的局部二元模式（LBP）作為紋理特徵。在特徵空間中，我們測量了相鄰圖像的距離，並把它視為一個位於二維平面上的開放輪廓上的點。 然後，我們採用一個無參數的關鍵點檢測方法檢測在視頻片段上的突變關鍵點。基於這些突變關鍵點，我們對膠囊內窺鏡視頻進行分割。最後，在每段被分割的視頻片段上，我們通過提取有代表性的關鍵幀來實現膠囊內窺鏡視頻摘要。我們分別用模擬和真實的病人數據進行實驗，對提出的方法進行驗證，結果表明了我們所提出的方案的有效性。它在實現自動評估膠囊內窺鏡圖像上具有很大的潛力。 / Wireless Capsule Endoscopy (CE) is a non-invasive technology to inspect the whole gastrointestinal (GI) tract, especially the small intestine. It has dramatically changed the way of diagnosis and management of many diseases of the small intestine, such as obscure gastrointestinal bleeding, Crohn’s disease, small bowel tumors, polyposis syndromes, etc. Despite its promising clinical findings, it still has some limitations. The main problem is that it requires manual assessment of approximately 50,000 low quality images per examination which is highly time-consuming and labor-intense. / CE analysis and assessment so far treated CE images as individual and independent observations. It is obviously not the case as there is often significant overlap among images. In particular, CE captures multiple views of the same anatomy as the capsule is slowly propelled by peristalsis. Our broader work aims to perform computer aided diagnosis (CAD) in endoscopy using all available information, including multiple images. / In this dissertation, a framework of multi-class Hidden Markov Models (HMM) embedded with statistical classifiers for combining information from multiple CE images is proposed. Due to the low quality of CE image, pre-processing is performed to enhance CE images by increasing the contrast and removing noises. Several image enhancement methods are investigated and customized for CE images. For frame-based supervised classification, AdaBoost is used as the ensemble classifier to combine multiple classifiers, i.e. support vector machine (SVM), k-nearest neighbor (k-NN), and Bayes classifier. Before classification, color, edge and texture features are extracted and fused. Finally, both supervised and unsupervised methods are proposed for CE study synopsis. For supervised method, a flexible and extensible framework based on HMM is developed to integrate temporal information in CE images. It can be extended to multi-class, multi-features, and multi-states. Improvements can be made by combined HMM and Parallel HMM (PHMM) which are introduced as decision-level fusion schemes. Combined HMM considers different sources via a multi-layer HMM model to perform classification and video synopsis. PHMM employs Bayesian inference to combine the recognition results at decision level. For unsupervised method, illumination-independent opponent color moment invariants and local binary pattern (LBP) based on Contourlet transform are explored as color and texture features, respectively. Pair-wise image dissimilarity is measured in the feature space and treated as points on an open contour in a 2-D plane. CE video is segmented based on sudden change points which are detected using a non-parametric key-point detection method. From each segment, representative frames are extracted to summarize the CE video. Validation results on simulated and real patient data show promising performance of the proposed framework. It has great potential to achieve automatic assessment for CE images. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhao, Qian. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 142-175). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.ii / Acknowledgments --- p.vii / List of Tables --- p.xiii / List of Figures --- p.xv / Chapter 1 --- The Relevance of Synopsis --- p.1 / Chapter 1.1 --- Problem Statement --- p.1 / Chapter 1.2 --- Application - Capsule Endoscopy Assessment --- p.4 / Chapter 1.3 --- Literature Review --- p.9 / Chapter 1.3.1 --- Methods Based on Frame Classification --- p.11 / Chapter 1.3.2 --- Methods Integrating Temporal Information --- p.14 / Chapter 1.4 --- Contributions --- p.19 / Chapter 1.5 --- Organization --- p.23 / Chapter 2 --- Preliminary --- p.25 / Chapter 2.1 --- Hidden Markov Model (HMM) --- p.25 / Chapter 2.2 --- Factorial HMM --- p.35 / Chapter 3 --- Temporal Integration in Capsule Endoscopy Image Analysis --- p.37 / Chapter 3.1 --- Pre-processing --- p.38 / Chapter 3.2 --- Feature Extraction --- p.43 / Chapter 3.3 --- Frame-based Supervised Classification --- p.47 / Chapter 3.3.1 --- Supervised Classification using Individual Frames --- p.47 / Chapter 3.3.2 --- Ensemble Learning Based on AdaBoost --- p.50 / Chapter 3.4 --- Sequence-based Supervised Classification --- p.52 / Chapter 3.5 --- Experiments --- p.58 / Chapter 3.5.1 --- Capsule Endoscopy Image Enhancement --- p.60 / Chapter 3.5.2 --- Frame-based Supervised Classification --- p.67 / Chapter 3.5.3 --- Image Sequence Classification --- p.68 / Chapter 3.6 --- Discussion --- p.80 / Chapter 3.7 --- Summary --- p.82 / Chapter 4 --- Capsule Endoscopy Study Synopsis --- p.98 / Chapter 4.1 --- Supervised Synopsis Using Statistical Models --- p.98 / Chapter 4.2 --- Unsupervised Synopsis via Representative Frame Extraction --- p.100 / Chapter 4.2.1 --- Feature Extraction --- p.100 / Chapter 4.2.2 --- Non-parametric Key-point Detection --- p.111 / Chapter 4.2.3 --- Representative Frame Extraction --- p.112 / Chapter 4.3 --- Experiments --- p.119 / Chapter 4.3.1 --- Supervised Synopsis Based on HMM --- p.119 / Chapter 4.3.2 --- Unsupervised Synopsis --- p.125 / Chapter 4.4 --- Discussion --- p.132 / Chapter 4.5 --- Summary --- p.133 / Chapter 5 --- Conclusions and Future Work --- p.138 / Chapter 5.1 --- Conclusions --- p.138 / Chapter 5.2 --- Future Work --- p.141 / Bibliography --- p.142

A feature extraction approach based on color is firstly proposed. Exploiting color histogram of an image, we can obtain distribution of different colors in images. Then we employ minimum distance classifier based on a new distance criterion to judge status of regions. In this section, we also validate benefits of WCE image enhancement to the proposed CAD system. / Finally, we propose a new approach of chrominance moment as another kind of feature to discriminate normal regions from abnormal regions, which makes full use of Tchebichef polynomials and HSI color space. This new feature extraction scheme preserves illumination invariance without numerical approximation. / In conclusion, this thesis investigates several major and challenging problems such as WCE images enhancement and feature extractions in CAD for WCE images, and proposes several novel schemes to solve those problems. Extensive experiments are reported to demonstrate effectiveness of the proposed algorithms. / Next, we investigate automatic diseases detection for WCE images to partially solve the second problem. In this part we explore different features that are suitable for detection of diseases from three viewpoints, i.e., color, texture and chromaticity, because clinicians mainly use these clues to diagnose. At the same time, we introduce their corresponding classifiers. / We further advance a new texture feature extraction method, curvelet based local binary pattern, to detect abnormal regions in WCE images. This method takes advantage of curvelet transform and local binary pattern to describe textural features of WCE images. / Wireless capsule endoscopy (WCE) is a state-of-the-art technology to diagnose gastrointestinal (GI) tract diseases without invasiveness. However, there exist two major problems concerning WCE images. One problem is that many images for diagnosis have rather low contrast and are noisy, which causes difficulties to diagnosis and also to computer-aided detection, so it is necessary to enhance these images. The other one is that the viewing process of video data per examination is very time consuming because of the great amount of video data. If we can use computerized methods to help the physicians detect some abnormal regions in WCE images, it will certainly reduce the burden of physicians. Focusing on these two goals, this thesis mainly studies some main challenging problems in computer-aided diagnosis (CAD) system for WCE images. To solve the first problem, we put forward an adaptive curvature strength diffusion method to enhance WCE images. Based on local characteristics analysis of WCE images, we propose a new concept of curvature strength. Then, we employ curvature strength diffusion to enhance WCE images with an adaptive choice of conductance parameter. Finally, we extend the curvature strength diffusion to color space since WCE images are color images. / Li, Baopu. / Adviser: Max Q. H. Meng. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3640. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 126-150). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

This study is intended to determine the feasiblity of establishing a high-quality, free-standing MR imaging center dedicated to the breast in or about the City of Redlands.

Iron oxide nanoparticles are of great interest as contrast agents for research and potentially clinical molecular magnetic resonance imaging (MRI). Biochemically modifying the surface coatings of the particles with proteins and polysaccharides enhances their utility by improving cell receptor specificity, increasing uptake for cell labeling and adding therapeutic molecules. Together with the high contrast they produce in MR images, these characteristics promise an expanding role for iron oxide nanoparticles and molecular MR imaging for studying, diagnosing and treating diseases at the molecular level. However, these contrast agents produce areas of signal loss with traditional MRI sequences that are not specific to the nanoparticles and cannot easily quantify the contrast agent concentration. With the expanding role of iron oxide nanoparticles in molecular imaging, new methods are needed to produce a quantitative contrast that is specific to the iron oxide nanoparticle. This dissertation presents a new method for detecting and quantifying iron oxide nanoparticles using an adiabatic preparation pulse and the failure of the adiabatic condition for spins diffusing near the particles. In the first aim, the theoretical foundation of the work is presented, and a Monte Carlo simulation supporting the proposed mechanism of the contrast is described. Adiabatic pulse prepared imaging sequences are also developed for imaging at 3 Tesla and 9.4 Tesla to highlight the translational potential of the approach for clinical examinations and scientific research, and the linear correlation of the contrast with iron concentration ideal for quantification is presented. Further, the physical characteristics of the nanoparticles and the parameters of the MRI sequence are modified to characterize the approach. In the second aim, the contrast is characterized in more realistic phantoms and in vitro, and a method to more accurately quantify nanoparticle concentration in the presence of magnetization transfer is presented. Finally, accelerated imaging methods are implemented to acquire the adiabatic contrast in a time compatible with in vivo imaging, and the technique is evaluated in an in vivo model of quantitative iron oxide nanoparticle imaging. Together, these aims present a method using an adiabatic preparation pulse to generate an MR contrast based on the microscopic magnetic field gradients surrounding the iron oxide nanoparticles that is suitable for in vivo quantitative, molecular imaging.