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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Automated screening of ultrasound images for carcinoma of liver.

January 1996 (has links)
by Wun Yuk Tsan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 121-129). / ABSTRACT --- p.i / ACKNOWLEDGMENT --- p.iii / TABLE OF CONTENTS --- p.iv / TABLE OF FIGURES AND TABLES --- p.vi / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Ultrasonography in Clinical Medicine --- p.1 / Chapter 1.1.1 --- Ultrasonic features of the liver --- p.1 / Chapter 1.1.2 --- Image artifacts in liver ultrasonograms --- p.4 / Chapter 1.1.3 --- Characteristics of liver ultrasonic image --- p.6 / Chapter 1.2 --- Liver Carcinoma in Hong Kong --- p.9 / Chapter 1.2.1 --- Morphological features of liver carcinoma --- p.10 / Chapter 1.2.2 --- Ultrasonographic features of liver carcinoma --- p.11 / Chapter 1.3 --- Ultrasonography and Computer --- p.12 / Chapter 1.4 --- Objectives of Thesis --- p.14 / Chapter 1.4.1 --- Hypothesis of the thesis --- p.15 / Chapter 1.4.2 --- Methods of experiment --- p.15 / Chapter 1.5 --- Organization of this Thesis --- p.17 / Chapter CHAPTER 2: --- COMPUTERIZED MEDICAL IMAGING: A REVIEW --- p.19 / Chapter 2.1 --- Computer Vision and Medical Imaging --- p.19 / Chapter 2.1.1 --- Artificial intelligence --- p.21 / Chapter 2.1.2 --- Mathematics models --- p.23 / Chapter 2.2 --- Computer Vision and Ultrasonic Images of Liver --- p.25 / Chapter 2.2.1 --- Studies on radiofrequency (RF) --- p.25 / Chapter 2.2.2 --- Studies on amplitude derived data --- p.26 / Chapter 2.3 --- Implications of Previous Work --- p.28 / Chapter 2.4 --- Limitations of Previous Work --- p.30 / Chapter CHAPTER 3: --- STATISTICAL TEXTURE --- p.32 / Chapter 3.1 --- Statistical Textural Analysis --- p.32 / Chapter 3.2 --- Statistical Texture for Segmentation --- p.34 / Chapter 3.3 --- Statistical Features Studied in This Research --- p.35 / Chapter 3.3.1 --- First-order statistics --- p.35 / Chapter 3.3.2 --- Second-order statistics --- p.36 / Chapter 3.3.3 --- Higher-order statistics --- p.41 / Chapter 3.4 --- Novel Statistical Texture Features --- p.42 / Chapter 3.5 --- Stable Statistical Textures: A New Hypothesis --- p.43 / Chapter 3.6 --- Centroids of Statistical Texture Descriptors --- p.45 / Chapter CHAPTER 4: --- NORMAL LIVER IMAGES --- p.48 / Chapter 4.1 --- Further Description of Normal Liver USG --- p.48 / Chapter 4.1.1. --- Equalized images --- p.50 / Chapter 4.2 --- Stable Statistical Descriptors in Normal Liver Images --- p.50 / Chapter 4.3 --- Clustering Algorithm --- p.53 / Chapter 4.3.1. --- Accuracy of the algorithm --- p.58 / Chapter 4.3.2 --- The algorithm and ultrasound artifacts --- p.60 / Chapter 4.3.3 --- Fuzzy algorithm for clustering --- p.62 / Chapter 4.4 --- Evaluation of the Algorithm --- p.63 / Chapter CHAPTER 5: --- IMAGES OF LIVER CARCINOMA --- p.64 / Chapter 5.1 --- Characteristics of Liver Carcinoma --- p.64 / Chapter 5.2 --- Algorithm for Tumour Detection --- p.65 / Chapter 5.2.1 --- Which statistical descriptors to use? --- p.66 / Chapter 5.2.2 --- How to isolate the capsules subimages? --- p.68 / Chapter 5.2.3 --- How to estimate the position of the tumour cells in the descriptor curve? --- p.72 / Chapter 5.2.4 --- Refinements of the algorithm --- p.73 / Chapter 5.3 --- Results of the Algorithm --- p.75 / Chapter 5.4 --- Further Examples --- p.80 / Chapter 5.5 --- Evaluation of the Algorithm --- p.87 / Chapter 5.5.1 --- Time required by the algorithm --- p.87 / Chapter 5.5.2 --- Sensitivity --- p.88 / Chapter 5.5.3 --- False positives and negatives --- p.88 / Chapter CHAPTER 6: --- REVIEW AND PROSPECTS --- p.90 / Chapter 6.1 --- Conclusions --- p.91 / Chapter 6.1.1. --- The objectives --- p.91 / Chapter 6.1.2 --- Hypotheses --- p.91 / Chapter 6.1.3. --- Statistical features --- p.92 / Chapter 6.2 --- Evaluation --- p.93 / Chapter 6.2.1 --- Noises --- p.93 / Chapter 6.2.2 --- Statistical features --- p.94 / Chapter 6.2.3 --- Methodology --- p.96 / Chapter 6.3 --- Future Work and Research --- p.98 / Chapter 6.3.1 --- Implementation and further development of the system --- p.98 / Chapter 6.3.2 --- Future research of the system --- p.99 / Chapter 6.3.3 --- Fuzzy algorithm --- p.100 / Chapter 6.3.4 --- Further work on statistical texture features --- p.100 / Chapter 6.3.5 --- The commercial potential of the system --- p.100 / Chapter 6.4 --- Final Conclusion --- p.101 / APPENDICES --- p.102 / Appendix A: Program Listings --- p.102 / Listing 1: pcx.c --- p.103 / Listing 2: feature.c --- p.108 / "Listing 3: detect, c" --- p.108 / Listing 4: centroid. c --- p.117 / AppendexB: Further Readings --- p.120 / Chapter I. --- Textbooks on Computer Vision or Images --- p.120 / Chapter II. --- Reference Books on Processing Algorithms in C Language --- p.120 / REFERENCES --- p.121

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