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研究生:沈偉誌
研究生(外文):Wei-Chih Shen
論文名稱:植基於BI-RADS之乳房超音波電腦輔助診斷與分類之研究
論文名稱(外文):Study on Computer-Aided BI-RADS iagnosis and Classification for Breast Ultrasound
指導教授:張瑞峰張瑞峰引用關係
指導教授(外文):Ruey-Feng Chang
學位類別:博士
校院名稱:國立中正大學
系所名稱:資訊工程所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:96
語文別:英文
論文頁數:113
中文關鍵詞:乳房超音波影像之分析與研究
外文關鍵詞:BI-RADScomputer-aided classificationcomputer-aided diagnosisbreast ultrasound
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隨著電腦科技的快速發展,釵h的研究學者嘗試發展電腦輔助診斷系統來幫助醫師辨識腫瘤的良惡性,但是在臨床診斷中,醫師根據BI-RADS所定義的描述符號來描述腫瘤的特徵,並且根據描述結果估計腫瘤的惡意可能性,將腫瘤分為很可能為良性、疑似病灶、以及高度懷疑為惡性三種處置類別。
在本研究中,我們發展一個電腦應用系統模擬醫生的臨床診斷工作,首先,將BI-RADS所定義的超音波特徵描述符號數學化的量化並且評估這些電腦化的BI-RADS特徵在電腦輔助診斷系統中的效能表現,然後,提出一個可以判讀來自不同超音波系統影像的電腦輔助分類系統,相對於現有發展的電腦輔助診斷系統,無法明確判讀的腫瘤被歸類為不確定類別等待進一步的病理證實,此外,我們也探討了空間複合成像技術對於電腦輔助診斷系統效能的影響。
在提出電腦化的特徵中,邊界的起伏與角狀特徵對於電腦輔助診斷或是分類系統的貢獻是最顯著的,醫生與提出的電腦輔助分類系統之間的分類結果具有高度的一致性,並且提升專一度(Specificity)達8.85%,與一般電腦輔助診斷系統相比,提升敏感度(Sensitivity)達10.5%,並且,我們證實了空間複合成像技術雖然可以提昇影像品質,但是無法提昇電腦輔助診斷系統的診斷效能。
With the rapid development of computer applications, many researchers attempt to developed a computer-aided diagnosis (CAD) system to help the radiologists for differentiating the benign from malignant masses. In the clinical diagnosis, radiologists, however, classify the masses into assessment categories probably benign, suspicious abnormality, and highly suggestive of malignancy according to the likelihood of malignancy which is evaluated by the descriptions of mass sonographic characteristics defined in BI-RADS.
In this thesis, the clinical diagnosis process of radiologists was simulated as the computer application system. Firstly, the descriptive items of sonographic characteristics defined in BI-RADS were mathematically quantified and the diagnostic performance of proposed computerized BI-RADS features for CAD system were measured. Then, a computer-aided classification (CAC) system which could be used to diagnose the cases acquired form different ultrasound systems was proposed. Compared with the currently developed CAD systems, the indeterminate cases were classified to category suspicious abnormality for further proving in the proposed CAC system. Besides, the influences of spatial compound imaging technique for the diagnostic performances of CAD system was assessed.
In the proposed computerized BI-RADS features, the contributions of margin characteristics, lobulate and angular, was the most significant for the diagnostic performances of CAD system and that of CAC system. The interobserver agreement between the radiologists and the CAC system was indicated as substantial agreement. Compared with the radiologists, the specificity was improved by 8.85% in the proposed CAC system. Compared with the conventional CAD system, the sensitivity was improved by 10.5% in the proposed CAC system. And, we concluded that the spatial compound imaging technique not implies the improving of diagnostic performance for CAD system even though the quality of ultrasound images were improved.
Table of Contents

Abstract in Chinese I
Abstract in English II
Acknowledgement IV
List of Figures VIII
List of Tables XI

Chapter 1 Introduction 1
1.1 Research Motivation 1
1.2 Survey of Related Researches 2
1.2.1 Clinical Diagnosis for Radiologists 2
1.2.2 Sonographic Characteristics Used in Computer-Aided Diagnosis Systems 5
1.2.3 Classification and Regression 10
1.2.4 Statistical Analysis 14
1.2.5 To Assess the Influences of Spatial Compound Imaging for Radiologists 15
1.3 Overview of Proposed Approach 16
1.4 Major Contribution of the thesis 17
1.5 Thesis Organization 18

Chapter 2 Breast Ultrasound Computer-Aided Diagnosis Using BI-RADS Features 21
2.1 Introduction 21
2.2 Materials and methods 24
2.2.1 Data Acquisition 24
2.2.2 Computerized BI-RADS features 25
2.2.3 Experimental method and performance evaluation 32
2.3 Result 34
2.3.1 Data analysis of computerized BI-RADS features 34
2.3.2 Computer-aided diagnosis using all computerized BI-RADS features 35
2.4 Discussion 35
2.4.1 Diagnostic value of each computerized BI-RADS feature in the CAD system 35
2.4.2 Critical thresholds on Angular and degree of abrupt interface characteristics 36
2.5 Conclusion and future works 40

Chapter 3 Computer Aided Classification System for Breast Ultrasound Based on BI-RADS 42
3.1 Introduction 42
3.2 Materials and methods 45
3.2.1 Computerized BI-RADS features 46
3.2.2 Machine-dependent factors 54
3.2.3 Weighting Strategy 55
3.3 Results and Discussion 57
3.3.1 Radiologists’ classification result 57
3.3.2 Data analysis of the proposed BI-RADS features 58
3.3.3 Basic CAC system 60
3.3.4 Weighted CAC system 61
3.3.5 Performance comparisons of conventional CAD and weighted CAC systems 63
3.4 Conclusion and future studies 64

Chapter 4 Diagnostic performance of Computer-Aided Diagnosis System : Conventional US versus Spatial Compound Imaging 66
4.1 Introduction 66
4.2 Materials and Methods 69
4.2.1 Data Acquisition 69
4.2.2 Computerized BI-RADS features 69
4.2.3 Experimental methods and performance evaluation 75
4.3 Result 77
4.3.1 Data analysis of the evaluations in conventional US and spatial compound imaging 77
4.3.2 Diagnostic performance of CAD systems at conventional US and at spatial compound imaging 79
4.3.3 Diagnostic performance of CAD systems in crossing ultrasound techniques 82
4.4 Discussion 83

Chapter 5 Conclusions and Future Works 86
5.1 Conclusions 86
5.2 Future works 88

Chapter 6 References 90
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