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Three-dimensional structure reconstruction from tomographic views.January 1996 (has links)
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
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Adequacy of consenting patients for computed tomography (CT) scans in a developing country: a survey of two academic hospitals in Johannesburg, South AfricaShayingca, Thandaza Mitchel 27 March 2015 (has links)
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.
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Computerised microtomography : non-invasive imaging and analysis of biological samples, with special reference to monitoring development of osteoporosis in small animals /Stenström, Mats, January 1900 (has links)
Diss. (sammanfattning) Linköping : Univ., 2001. / Härtill 5 uppsatser.
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Computed tomography demonstration of the complications and associations of lymphobronchial tuberculosis in childrenLucas, Susanna 03 April 2012 (has links)
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.
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The distribution and volume of visceral and subcutaneous adipose tissue, derived from CT examination.January 1998 (has links)
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
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Development of a thermal neutron imaging facility for real time neutron radiography and computed tomography /Jo, Young Gyun, January 1998 (has links)
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.
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Rigid, multi-rigid, and non-rigid image registration of skeletal structures /Hu, Yangqiu. January 2005 (has links)
Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 101-107).
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Brain computed tomography findings in HIV-infected adults presenting with impaired mental status: determining the value of CT in a resource constrained environment.Sewchuran, Tanusha 28 March 2014 (has links)
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.
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Temporomandibular joint X-ray computed tomography methodology and clinical applications /Christiansen, Edwin L. January 1988 (has links)
Thesis (doctoral)--Karolinska Institutet, Stockholm, 1988. / Extra t.p. with thesis statement inserted. Includes bibliographical references.
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Enhancement in Low-Dose Computed Tomography through Image Denoising Techniques: Wavelets and Deep LearningUnknown Date (has links)
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
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