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研究生:黃怡銘
研究生(外文):Yi-Ming Huang
論文名稱:肝硬化超音波影像紋理的統計比較分析
論文名稱(外文):Statistical Comparisons of Echo-Textures for Liver Cirrhosis in Ultrasound Images
指導教授:盧鴻興盧鴻興引用關係
指導教授(外文):Henry Horng Shing Lu
學位類別:碩士
校院名稱:國立交通大學
系所名稱:統計所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:1999
畢業學年度:87
語文別:中文
論文頁數:78
中文關鍵詞:肝硬化超音波影像紋理統計比較分析
外文關鍵詞:CirrhosisEcho-Textures in Ultrasound ImagesStatsitcal Comparisons
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超音波照影是初期肝硬化的診斷工具之一,可以藉由比較同一病人肝與脾的超音波影像紋理來判定此病人是否患有肝硬化。本篇論文研究新的統計比較分析方法,應用在台大醫院內科視鏡超音室收集來的臨床超音波影像資料上。我們結合不同的影像特徵選取方法、降維度工具及統計分類規則,然後運用Jackknife和Bootstrap的方法來估計影像分類誤差以找尋最佳的肝硬化超音波影像分析方法。

Ultrasound images are one of the main diagnosis tools for early detection and regular check ups for liver cirrhosis. By comparing the echo-textures of liver and the accompanied spleen of the same person at the same scan, the variations between subjects, systems and machines are under control. This study proposes new statistical comparison methods for this purpose based on the clinic data collected at the National Taiwan University Hospital. The Jackknife and bootstrap prediction errors for different methods are investigated. Different combinations of feature selections, dimension reduction techniques and classification rules are studied and reported.

1 Introduction.................................................1
2 Diagnosis Criteria of Liver Cirrhosis in Ultrasonic Images...3
2.1 Medical Criteria........................................3
2.2 Computer Assisted Comparisons of Echo-Textures of Livers and Spleens....................................................5
3 Feature Selections of Ultrasonic image.......................6
3.1 Local Blocks in the Space Domains........................6
3.2 Local Blocks in the Frequency Domain.....................7
3.3 Local Blocks in the Space-Frequency Domain...............9
4 Dimension Reduction Techniques..............................14
4.1 Principal Component Analysis (PCA)......................14
4.2 Sliced Inverse Regression (SIR).........................15
5 Construction Methods of Classification Rules................17
5.1 Model Checking..........................................17
5.2 Discriminant Analysis...................................17
6 Empirical Studies Based on Simple Heuristic Methods.........20
6.1 Individual Statistics of Liver and Spleen Images........20
6.2 Pairwise Comparisons of Liver and Spleen Images.........26
7 Classification with Dimension Reduction Techniques..........31
7.1 Projection onto the PCA Directions of Livers and Spleens31
7.2 Projection onto the PCA Directions of Spleens...........39
7.3 Projection onto the SIR Directions of Livers and Spleens47
8 Jackknife and Bootstrap Estimates of Error Rates............51
8.1 Jackknife Estimates.....................................51
8.2 Bootstrap Estimates.....................................51
8.3 Empiric Results.........................................52
9 Conclusion and Discussion74

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