臺灣博碩士論文加值系統

乳癌是全世界女性最常發生的癌症之一。及早發現癌症可以得到較適當的治療。近十年來，由於超音波的便利性及對人體較無傷害，超音波檢測在對乳癌的篩檢及診斷上一直扮演著很重要的角色。然而，由於超音波探頭沒辦法完全涵遝蒤茖觼苤A相對於X光乳房攝影來說並不是很方便的篩檢工具。在本篇論文中，我們提出一種影像縫合技術來合併3-Pass影像成完整乳房影像。除此之外，我們也提出完全不用人為介入的全自動篩檢系統。首先使用取樣的技術來縮短系統處理時間。由於超音波影像本身有強烈的雜訊，我們使用非等向性擴散模糊的方式來過濾班點雜訊，並以細棒演算法來強化邊界資訊。接著使用灰階分切方法將影像分為釵h區域，並且用一些事先定義的條件來找出可能為腫瘤的區域。在作為測試的25個病例中，幾乎所有腫瘤或水泡都能被正確找到，而平均每個病例會產生兩個誤判。依實驗結果，我們驗證的這個系統的準確性。

Breast cancer is one of the most common cancers among women all over the world. The early detection of the cancer provides a better chance of proper treatment. In the last decade, ultrasound imaging plays an important role in the field of breast cancer diagnosis because of its convenience and non-invasive. However, the ultrasound probe does not fully cover the breast width, it is not a convenient screening tool when adjunct with screening mammography. In this paper, an image stitching technique is proposed to stitch multi-pass images into a full-view image. In addition, a fully automatic screening system for whole breast with absolutely no human intervention is proposed. In order to reduce the processing time, the subsampling method is firstly used to accomplish the whole screening work as soon as possible. Owing to US images always have strong speckle noise, some preprocessing techniques, such as anisotropic diffusion filter and stick operator , are applied to reduce speckle noise and enhance the edges in the US image. Then, a thresholding measure based on gray-level slicing is used to partition the US image into several regions, and the suspicious tumor regions are determined according to some pre-defined criteria. By examining the US test database consisted of 25 cases, almost all the tumors or cysts could successfully be detected when an average of two false positive for each case is produced. A free-response operative characteristics (FROC) curve is also used to evaluated the performance. The experimental results show that the proposal system gives quite satisfactory detection performance.

摘 要 I
ABSTRACT II
ACKNOWLEDGEMENTS I
LIST OF TABLES VII
LIST OF TABLES VII

CHAPTER 1 INTRODUCTION 1
CHAPTER 2 WHOLE BREAST ULTRASOUND AND IMAGE REGISTRATION 5
2.1 Whole Breast Ultrasound 5
2.2 Image Registration 8
CHAPTER 3 IMAGE STITCHING AND AUTOMATIC SCREENING SYSTEM 10
3.1 Image Stitching Procedure 10
3.1.1 Three-pass US Images 10
3.1.2 Spatial Registration Algorithm 12
3.1.3 Temporal Alignment Step 16
3.2 Automatic Screening System 18
3.2.1 Reducing Diagnosis Time 19
3.2.2 Pre-processing 21
3.2.3 Gray-level Slicing 25
3.2.4 Tumor Criteria 27
CHAPTER 4 EXPERIMENTS AND RESULTS 38
4.1 Experimental Results 38
4.2 Discussion 49
CHAPTER 5 CONCLUSION 51

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