by Ho, Chi-Kin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 62-64). / Chapter 1 --- Introduction / Chapter 2 --- Previous Work --- p.2-1 / Chapter 2.1 --- Thresholding --- p.2-1 / Chapter 2.2 --- Edge Detection --- p.2-2 / Chapter 2.3 --- Region Growing --- p.2-2 / Chapter 2.4 --- Radial Contour Model --- p.2-3 / Chapter 2.5 --- Regularized Region Contrast --- p.2-3 / Chapter 2.6 --- Deformable Model --- p.2-4 / Chapter 3 --- The ODD-Balloons Model --- p.3-1 / Chapter 3.1 --- Design Rationale --- p.3-1 / Chapter 3.2 --- Overview --- p.3-5 / Chapter 3.3 --- 2-D Deformations --- p.3-8 / Chapter 3.4 --- Orthogonal Cut and Volume Transfer --- p.3-11 / Chapter 3.5 --- Smoothing Operation --- p.3-17 / Chapter 3.6 --- Properties --- p.3-20 / Chapter 3.6.1 --- Conformation to 3-D Shape --- p.3-20 / Chapter 3.6.2 --- Noise Sensitivity --- p.3-20 / Chapter 3.6.3 --- Convergence and Efficiency --- p.3-22 / Chapter 3.6.4 --- Easy-to-Use --- p.3-23 / Chapter 3.7 --- Summary --- p.3-24 / Chapter 4 --- Experiment Results --- p.4-1 / Chapter 4.1 --- Synthetic Data Experiments --- p.4-1 / Chapter 4.2 --- Real Data Experiment --- p.4-3 / Chapter 4.3 --- Discussions --- p.4-6 / Chapter 5 --- Conclusion and Future Work --- p.5-1 / Chapter 5.1 --- Conclusion --- p.5-1 / Chapter 5.2 --- Recommended Future Work --- p.5-2 / Appendix A Discrete Implementation of 2-D Deformation --- p.A-1 / Appendix B Choosing Elasticity and Rigidity Coefficients of 2-D Deformation --- p.B-1 / Bibliography --- p.BIB-1

A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Medicine in Diagnostic Radiology Johannesburg, 2014 / INTRODUCTION South Africa presents a complex scenario with regard to patients consenting for medical procedures, because of the differing profiles of the population and the health care workers who perform the consenting procedures. AIM To evaluate consenting practice for CT scanning, within the South African tertiary referral setting and to determine if there are any associations between patient demographic profile and the level of understanding with the adequacy of consent. METHOD A prospective survey regarding consenting practices for CT scanning was performed in a form of an interview questionnaire in patients presenting to Chris Hani Baragwanath Academic and Charlotte Maxeke Johannesburg Academic hospitals. Determination of any associations between patient age, racial group, language and education was made with the level of understanding and adequacy of consent. RESULTS The survey was conducted on 117 patients; 86 from Charlotte Maxeke Johannesburg Academic Hospital and 31 from Chris Hani Baragwanath Academic Hospital. We found no significant association between gender and age category (p=0.11), racial group (p=0.17), education (p=0.26), home language (p=0.21) or residential area type (p=0.70). vi There was a significant, weak, association between age category and education (p=0.043; Cramer’s V=0.29). There was a significant, moderate association between the understanding of the language of consent and the home language of the patients (p=0.0013; phi coefficient=0.43). There was also some association between education and age. Just over 50% of patients felt that they had been given enough information and had had an opportunity to ask questions and only 33% had been offered an alternative to the CT scan. There was a significant difference in the mean adequacy of consent score with regards to racial group (p<0.0001), home language (p=0.0073), residential area type (p<0.0001) and level of education (p<0.0001). CONCLUSION Language differences between patients and personnel performing the consent procedure proved to be a major barrier in offering adequate consenting for CT Scans.

Diss. (sammanfattning) Linköping : Univ., 2001. / Härtill 5 uppsatser.

M.Med. (Radiology), Faculty of Health Sciences, University of the Witwatersrand, 2011 / Lymphobronchial tuberculosis (LBTB) is tuberculous lymphadenopathy involving the airways, which is particularly common in children. AIM: To describe the CT findings of LBTB in children, the parenchymal complications and associated abnormalities. METHOD: CT scans of 98 children with LBTB were retrospectively reviewed. Lymphadenopathy, bronchial narrowing, parenchymal complications and associations were documented. RESULTS: Infants comprised 51% of patients. The commonest lymphadenopathy was subcarinal (97% of patients). Bronchial compressions (259 in total) were present in all patients, of which 23% were severe / complete stenoses and 28% affected bronchus intermedius. Parenchymal complications were present in 94% of patients, including consolidation (88%), breakdown (42%), air trapping (38%), expansile pneumonia (28%), collapse (17%) and bronchiectasis (9%), all predominantly right-sided (63%). Associations included oval focal bodies, miliary nodules, pleural disease and intracavitory bodies. CONCLUSIONS: The most important CT finding of children with LBTB is visible airway compression as a result of lymphadenopathy. CT of children with LBTB showed that airway compressions were more severe in infants and most commonly involved bronchus intermedius. Numerous parenchymal complications were documented, all showing rightsided predominance. Several associations were identified.

by Poon Mei Yu. / Thesis submitted in: Dec. 1997. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 127-132). / Abstract also in Chinese. / Declaration --- p.i / Acknowledgement --- p.ii / Table of Contents --- p.iii / Abbreviations --- p.xi / List of Figures --- p.xiv / List of Tables --- p.xvii / Abstract --- p.xxi / Introduction --- p.1 / Chapter Chapter 1: --- Obesity & related abnormalities --- p.2 / Chapter Chapter 2: --- Measurement of body fat --- p.11 / Objective --- p.18 / Chapter Chapter 3: --- Purpose of study --- p.19 / Method --- p.24 / Chapter Chapter 4: --- Technical considerations on CT technique --- p.25 / Chapter Chapter 5: --- Data Collection --- p.32 / Chapter Chapter 6: --- Data Analysis --- p.44 / Results --- p.49 / Chapter Chapter 7: --- Amount of adipose tissue --- p.50 / Chapter Chapter 8: --- "Adipose tissue distribution, VSR & VTR" --- p.81 / Discussion --- p.105 / Chapter Chapter 9: --- Discussion --- p.106 / Conclusions --- p.122 / Chapter Chapter 10: --- Conclusions --- p.123 / References --- p.127 / Appendix I --- p.133 / Appendix II --- p.136 / Appendix III --- p.139 / DECLARATION --- p.i / ACKNOWLEDGEMENT --- p.ii / TABLE OF CONTENTS --- p.iii / Brief Contents --- p.iii / Detailed Contents --- p.v / ABBREVIATIONS --- p.xi / LIST OF FIGURES --- p.xiv / LIST OF TABLES --- p.xvii / ABSTRACT --- p.xxi / INTRODUCTION --- p.1 / Chapter Chapter 1: --- OBESITY & RELATED ABNORMALITIES --- p.2 / Chapter 1.1 --- Adipose Tissue --- p.2 / Chapter 1.2 --- Classification of Adiposity --- p.3 / Chapter 1.3 --- Obesity --- p.5 / Chapter Chapter 2: --- MEASUREMENT OF BODY FAT --- p.11 / Chapter 2.1 --- Methods of Measuring Body Fat --- p.11 / Chapter 2.1.1 --- Non-imaging Methods --- p.12 / Chapter 2.1.2 --- Imaging Methods --- p.13 / Chapter 2.1.2.1 --- Plain radiograph --- p.13 / Chapter 2.1.2.2 --- Ultrasound --- p.13 / Chapter 2.1.2.3 --- Computed tomography --- p.14 / Chapter 2.1.2.4 --- Magnetic resonance imaging --- p.16 / OBJECTIVE --- p.18 / Chapter Chapter 3: --- PURPOSE OF STUDY --- p.19 / Chapter 3.1 --- Objectives --- p.19 / Chapter 3.2 --- Explanation --- p.20 / Chapter 3.2.1 --- Best level of AT area measurement --- p.21 / Chapter 3.2.2 --- Linear AT dimension --- p.22 / Chapter 3.2.3 --- Sex and age differences --- p.22 / Chapter 3.2.4 --- Difference in attenuation interval of fat --- p.23 / METHOD --- p.24 / Chapter Chapter 4: --- TECHNICAL CONSIDERATIONS ON CT TECHNIQUE --- p.25 / Chapter 4.1 --- Defining Anatomy --- p.25 / Chapter 4.1.1 --- Abdominal visceral cavity --- p.26 / Chapter 4.1.1.1 --- Diaphragm --- p.26 / Chapter 4.1.1.2 --- Pelvis --- p.26 / Chapter 4.1.1.3 --- Boundary at mid-potion --- p.27 / Chapter 4.1.2 --- Intra- and retro- peritoneal compartments --- p.28 / Chapter 4.2 --- Attenuation interval of fat --- p.29 / Chapter 4.2.1 --- Distinctive pixel value vs. attenuation interval --- p.30 / Chapter 4.2.2 --- Choice of interval --- p.30 / Chapter Chapter 5: --- DATA COLLECTION --- p.32 / Chapter 5.1 --- Subjects --- p.32 / Chapter 5.2 --- Acquisition --- p.33 / Chapter 5.3 --- Measurement --- p.34 / Chapter 5.3.1 --- AT area measurement --- p.35 / Chapter 5.3.2 --- Linear AT measurement --- p.38 / Chapter 5.3.2.1 --- Subcutaneous AT thickness --- p.38 / Chapter 5.3.2.2 --- Visceral AT thickness --- p.39 / Chapter Chapter 6: --- DATA ANALYSIS --- p.44 / Chapter 6.1 --- Tools --- p.44 / Chapter 6.2 --- Mathematical Assumptions --- p.45 / RESULTS --- p.49 / Chapter Chapter 7: --- AMOUNT OF ADIPOSE TISSUE --- p.50 / Chapter 7.1 --- AT Volumes --- p.50 / Chapter 7.1.1 --- In male and female subgroups --- p.50 / Chapter 7.1.2 --- VAT and SAT increase with TAT --- p.52 / Chapter 7.1.3 --- A VAT volume vs. VAT volume --- p.54 / Chapter 7.2 --- AT Areas at Various Anatomical Levels --- p.55 / Chapter 7.2.1 --- In male and female subgroups --- p.56 / Chapter 7.2.2 --- Correlation between AT volumes and areas --- p.62 / Chapter 7.2.3 --- Prediction of abdominal AT volumes from AT areas --- p.63 / Chapter 7.3 --- Linear AT Dimensions --- p.66 / Chapter 7.3.1 --- Linear SAT dimensions correlated to AT volumes --- p.66 / Chapter 7.3.2 --- Linear VAT dimensions correlated to AT volumes --- p.68 / Chapter 7.3.3 --- Prediction of abdominal SAT volume --- p.70 / Chapter 7.3.4 --- Prediction of abdominal A VAT volume --- p.71 / Chapter 7.3.5 --- Prediction of abdominal TAT volume --- p.72 / Chapter 7.4 --- "AT Measurements, Sex and Age" --- p.73 / Chapter 7.4.1 --- In whole study population --- p.73 / Chapter 7.4.2 --- In male and female subgroups --- p.75 / Chapter 7.5 --- Difference in Attenuation Interval --- p.79 / Chapter Chapter 8: --- DISTRIBUTION OF ADIPOSE TISSUE: VSR & VTR --- p.81 / Chapter 8.1 --- VSR --- p.81 / Chapter 8.1.1 --- Correlation --- p.82 / Chapter 8.1.2 --- Prediction --- p.83 / Chapter 8.1.3 --- Effect of attenuation interval --- p.84 / Chapter 8.1.3.1 --- On VSR value --- p.84 / Chapter 8.1.3.2 --- On correlation and prediction results --- p.86 / Chapter 8.2 --- VTR --- p.88 / Chapter 8.2.1 --- Correlation --- p.88 / Chapter 8.2.2 --- Prediction --- p.89 / Chapter 8.2.3 --- Effect of attenuation interval --- p.91 / Chapter 8.2.3.1 --- On VTR value --- p.91 / Chapter 8.2.3.2 --- On correlation and prediction results --- p.93 / Chapter 8.3 --- VSR vs. VTR --- p.95 / Chapter 8.4 --- "VSR, VTR, Sex and Age" --- p.96 / Chapter 8.4.1 --- Correlation --- p.99 / Chapter 8.4.2 --- Prediction --- p.100 / Chapter 8.4.3 --- VSR and VTR increase with age --- p.101 / DISCUSSION --- p.105 / Chapter Chapter 9: --- DISCUSSION --- p.106 / Chapter 9.1 --- Absolute AT Content (Amount) --- p.106 / Chapter 9.1.1 --- AT areas of various anatomical levels --- p.106 / Chapter 9.1.1.1 --- Correlated to AT volume --- p.107 / Chapter 9.1.1.2 --- Prediction of abdominal A T volume: best level --- p.107 / Chapter 9.1.2 --- Linear AT dimensions --- p.109 / Chapter 9.1.2.1 --- Correlated to AT volume --- p.109 / Chapter 9.1.2.2 --- Prediction of abdominal AT volume --- p.111 / Chapter 9.2 --- AT Distribution Indices: VSR and VTR --- p.112 / Chapter 9.2.1 --- The best level --- p.114 / Chapter 9.3 --- Sex and Age Difference --- p.114 / Chapter 9.3.1 --- absolute AT content --- p.114 / Chapter 9.3.2 --- VSR and VTR --- p.116 / Chapter 9.4 --- Difference in Attenuation Interval --- p.118 / Chapter 9.4.1 --- Absolute AT content --- p.118 / Chapter 9.4.2 --- VSR and VTR --- p.119 / Chapter 9.5 --- Limitations --- p.120 / Chapter 9.5.1 --- Study population --- p.120 / Chapter 9.5.2 --- Differentiation of compartments --- p.121 / CONCLUSIONS --- p.122 / Chapter Chapter 10: --- CONCLUSIONS --- p.123 / Chapter 10.1 --- Absolute AT Content in Abdomen --- p.123 / Chapter 10.2 --- Abdominal AT Distribution --- p.125 / Chapter 10.3 --- Effect of Attenuation Interval --- p.126 / REFERENCES --- p.127 / APPENDIX I: Comparison of study populations & scanning techniques --- p.133 / APPENDIX II: Comparison of definitions of attenuation interval of fat and anatomical compartments --- p.136 / APPENDIX III: Statistical summary of the adipose tissue measurements in this study --- p.139

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 209-211). Available also in a digital version from Dissertation Abstracts.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 101-107).

INTRODUCTION: HIV/AIDS is a global health problem, with Sub-Saharan Africa the most affected. “Neuro-AIDS” refers to the extensive neuropathological manifestations of the disease. Neuroimaging of the HIV-infected individual plays a fundamental role in their work-up. Limited resources, however, drive the development of imaging protocols based on clinical signs. ‘Confusion’ may or may not represent a significant presenting sign and needs to be investigated, as it is the basis of referral of a significant number of patients for CT scanning. AIM: To determine the frequency of positive findings of head CT in HIV-infected adults presenting with confusion with/without associated neurology, and correlate them with the degree of immunosuppression, presence of CSF abnormality and their ARV therapy status. METHOD: CT brain scans of adult patients, who were HIV-positive and presented with confusion in Johannesburg, Gauteng, were retrospectively reviewed. The neurological status, CD4 counts, LP results and their ARV therapy status were documented. RESULTS: 30% of our HIV-infected patients presented with confusion. There were 156 patients who were included. CT scans were abnormal in 81%. We found that ‘associated neurology’ was a weak predictor for abnormal CT, making it a poor screening tool. A positive LP was predictive of infection (p=0.04 for focal infection, p=0.03 for infected surface collection) and infarction (p<0.01) on CT. CD4 count, LP results and ARV therapy were found to be abnormal in the majority of patients. CONCLUSIONS: CT was abnormal in the majority of HIV-infected patients presenting with confusion. Neurology was an unreliable clinical indicator. A positive LP was a good predictor for CT evidence of infection and infarction. The clinical parameters such as CD4 counts, LP results and ARV therapy, were abnormal in the majority of patients. If any of these parameters are abnormal in a patient with a normal CT, we believe this should motivate for further imaging with MRI.

Thesis (doctoral)--Karolinska Institutet, Stockholm, 1988. / Extra t.p. with thesis statement inserted. Includes bibliographical references.

Reducing the amount of radiation in X-ray computed tomography has been an active area of research in the recent years. The reduction of radiation has the downside of degrading the quality of the CT scans by increasing the ratio of the noise. Therefore, some techniques must be utilized to enhance the quality of images. In this research, we approach the denoising problem using two class of algorithms and we reduce the noise in CT scans that have been acquired with 75% less dose to the patient compared to the normal dose scans. Initially, we implemented wavelet denoising to successfully reduce the noise in low-dose X-ray computed tomography (CT) images. The denoising was improved by finding the optimal threshold value instead of a non-optimal selected value. The mean structural similarity (MSSIM) index was used as the objective function for the optimization. The denoising performance of combinations of wavelet families, wavelet orders, decomposition levels, and thresholding methods were investigated. Results of this study have revealed the best combinations of wavelet orders and decomposition levels for low dose CT denoising. In addition, a new shrinkage function is proposed that provides better denoising results compared to the traditional ones without requiring a selected parameter. Alternatively, convolutional neural networks were employed using different architectures to resolve the same denoising problem. This new approach improved denoising even more in comparison to the wavelet denoising. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection