臺灣博碩士論文加值系統

乳房X光攝影是截至目前為止被認為早期偵測乳癌方法中，考量明確度及敏感度與成本因素效益評估上最為可行的方法。近年來在外科醫學的研究結果中顯示，乳房攝影中微鈣化群聚的外型輪廓與空間分佈的情形是作為惡性腫瘤診斷的重要指標依據，然而由於攝影時投影方式及乳房受擠壓的影響，在所得的乳房攝影影像中微鈣化群聚在三維立體空間分佈的關係經常是混淆不明確的，因此近期較先進乳房攝影技術發展的趨勢已朝向結合多個相位的乳房攝影結果作為三維立體重建的參考基礎。
本論文主要提出一個以模型為基礎之乳房X光攝影微鈣化群立體定位及重建的方法。利用乳房攝影中兩個不同相位的影像(頭腳相及斜側相影像)完成定位及重建的工作，同時發展由二維影像重建三維乳房表示方法及以參數為基礎的受擠壓變形乳房模型。我們首先以等高集合法切割出乳房的輪廓，並以此輪廓透過所提乳房模型作三維立體重建，進而利用遺傳演算法求得頭腳像及斜側像重建比對時所需的最佳參數，完成三維立體模型重建及微鈣化群的立體位置定位。本論文除了可協助醫師重建微鈣化群在乳房中三維空間的資訊，提昇診斷的準確性外，同時重建出病人的乳房立體模型，作為乳房重建之臨床醫學上術前評估重建乳房之體積、形狀及位置等資訊，提供術前模擬實體評估之解決方案，有效減少醫療上資源的浪費與整體效率的提昇。

Mammography (breast X-ray) is considered currently by far the best trade-off between specificity/sensitivity and cost for the detection of breast cancer in its early stages. It has been revealed that the shape of cluster and the spatial distribution of individual microcalcifications within it are important indicators of its malignancy in recent clinical researches. However, the three-dimensional (3-D) distribution is confounded in mammographic images of clustered microcalcifications with image projection and breast compression. Therefore, recent advances in mammographic technologies have led to new approaches to generate and combine multiple views of the breast for 3-D disease reconstruction.
In this project, we proposed a model-based method for reconstructing 3-D microcalcification clusters from two mammographic views (Cranio-Caudal, CC view and Medio-Lateral Oblique, MLO view). We develop a 3-D breast representation and a parameterised breast compression model reconstructed from two-dimensional images. The level-set method is first used to segment and identify the contour of breast region. The contour is then used to reconstruct the 3-D breast representation through the proposed parameterized breast model. Furthermore, generic algorithm is used to estimate the most optimal parameters for matching the two breast representation volumes reconstructed from two different mammographic views respectively. Corresponding calcifications in the two views are then matched using both the geometric constraint and the matching criterion to build the 3-D reconstructed clusters. The purpose of this project is to make a full size solid breast model to assist reconstruction of 3-D breast information and microcalcification cluster localization. Doctors can also use this solid model for process of evaluation and planning before the surgeries to promote the efficiency of diagnosis, medical treatment qualities and reduce the waste of medical resource.

書名頁 i
論文口試委員審定書 ii
論文授權書 iii
摘要 iv
Abstract v
誌 謝 vi
目 錄 vii
表目錄 ix
圖目錄 x

第一章 簡介 1
1.1 研究背景 1
1.2 研究動機與目的 3
第二章 等高集合法及遺傳演算法 7
2.1等高集合法 7
2.1.1零等高集合(Zero Level Set) 8
2.1.2等高集合演算法 10
2.2基因遺傳演算法 11
2.2.1基因遺傳演算法演化規則 12
2.2.2基因遺傳演算法特性 15
第三章 研究架構 17
3.1影像強化 17
3.2等高集合法速度函數設計 19
3.3 影像邊緣化 21
3.3.1 乳房X光攝影肌肉組織切除 22
3.3.2乳頭及胸腔壁位置判定 26
3.3.3乳房邊緣曲線封閉 27
3.4三維乳房立體重建 28
3.4.1頭腳相立體重建方法 30
3.4.2斜側相立體重建方法 31
3.4.3乳房重建比對 32
3.4.4三維重建 33
3.5微鈣化群聚三維立體定位 35
第四章 實驗分析 38
4.1影像邊緣化 38
4.2三維乳房立體重建 40
4.3微鈣化群聚三維立體定位 41
4.4三維乳房立體重建驗證 42
第五章 結論 49
5.1研究成果 49
5.2研究限制 49
5.3未來展望 50
參考文獻 51

[1]L. W. Bassett, “Mammographic analysis of calcifications,” Radio Clin. North Am., 1992, no. 30, pp. 93-105.
[2]M. Lanyi, Diagnosis and Differential Diagnosis of Breast Calcifications. Berlin, Germany: Springer-Verlag, 1986.
[3]J. N. Wolfe, Xeroradiography of the Breast. Springfield, IL: Thomas, 1982.
[4]H. P. Chan, B. Sahiner, K. L. Lam, N. Petrick, M. A. Helvic, M. M. Goodsitt, and D. D. Adler, “Computerized analysis of mammographic microcalcifications in morphological and texture feature spaces,” Med. Phys., vol. 25, pp. 2007–2019, 1998.
[5]Y. Jiang, R. M. Nishikawa, D. E.Wolverton, C. E. Metz, M. L. Giger, R. A. Schmidt, C. J. Vyborny, and K. Doi, “Malignant and benign clustered microcalcifications: automated feature analysis and classification,” Radiology, vol. 198, pp. 671–678, 1996.
[6]W. J. H. Veldkamp, N. Karssemeijer, and J. H. C. L. Hendriks, “Automated classification of clustered microcalcifications into malignant and benign types,” Med. Phys., vol. 27, no. 11, 2000.
[7]M. Lanyi, Diagnosis and Differential Diagnosis of Breast Calcifications. Berlin, Germany: Springer-Verlag, 1986.
[8]S. P. Bates, S. M. Astley, J. D. Davies, and S. Sharp, “Three-dimensional reconstruction and shape classification of microcalcification clusters in breast lesions,” in Proc. 3rd Int. Workshop Digital Mammography, Chicago, IL, 1996, pp. 239–244.
[9]L. T. Niklason, B. T. Christian, L. E. Niklason, D. B. Kopans, P. J. Slanetz, D. E. Castleberry, B. H. Opsahl-Ong, C. E. Landberg, and B. Giambattista, “Digital breast tomosynthesis: potentially a new method for breast cancer screening,” in Proc. 4th Int. Workshop Digital Mammography, Nijmegen, The Netherlands, 1998, pp. 51–56.
[10]A. D. A. Maidment, E. F. Conant, S. A. Feig, C. W. Piccoli, and M. Albert, “3-Dimensional analysis of breast calcifications,” in Proc. 3rd Int. Workshop Digital Mammography, Chicago, IL, 1996, pp. 245–250.
[11] T. Müller, R. Stotzka, A. Hochmuth, W. Eppler, and H. Gemmeke, “Volume reconstruction of clustered microcalcifications in mammograms,” in Proc. 4th Int. Workshop Digital Mammography, Nijmegen, The Netherlands, 1998, pp. 321–328.
[12]M.Yam, M. Brady, and R. Highnam, “Combining views of compressible tissue that are separated by a wide angle,” GB 0 006 598.7, 2000.
[13]M. Yam, M. Brady, R. Highnam, C. Behrenbruch, R. English, and Y. Kita, “Three-Dimensional Reconstruction of Microcalcification Clusters from Two Mammographic views,” IEEE Trans. Med. Imag. vol. 20, no. 6, pp. 479-489, June 2001.
[14]鍾國亮，影像處理與電腦視覺，東華書局出版，2002年。
[15]S. Osher and J. A. Sethian, “Fronts Propagating with Curvature Dependent Speed: Algorithms Based on Hamilton-Jacobi Formulation,” J. Comp. Physi., vol. 79, pp. 12-49, 1988.
[16]J. A. Sethian, Level set methods and fast matching methods: Evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, 2nd ed., Cambridge, UK: Cambridge University Press, 1999.
[17]Luis Ib´a˜nez, Will Schroeder, Lydia Ng, and Josh Cates, and Insight Software Consortium, ITK Software Guide, pp.363-365, Aug. 21, 2003.
[18]J. S. Suri, K. Liu, S. Singh, S. N. Laxminarayan, X. Zeng, and L. Reden, “Shape recovery algorithms using level sets in 2-D 3-D medical imagery a state-of-the-art review,” IEEE Trans. Info. Tech. Biomed., vol. 6, no. 1, pp. 8-28, Mar., 2002
[19]張家榮，「使用等高集合法對多目標移動物之研究」，私立元智大學電機工程研究所博士論文，民國九十年。
[20]R. C. Gonzalez and R. E. Woods, Digital Image Processing, second edition, Pearson Education, NEW JERSEY, USA, 2002.
[21]Sze Man Kwok, Ramachandran Chandrasekhar, Yianni Attikiouzel, and Mary T. Rickard, “Automatic Pectoral Muscle Segmentation on Mediolateral Oblique View Mammograms,” IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 23, NO. 9, SEPTEMBER 2004
[22]R. J. Ferrari, R. M. Rangayyan, J. E. L. Desautels, R. A. Borges, and A. F. Frère, ” Automatic Identification of the Pectoral Muscle in Mammograms,” IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 23, NO. 2, FEBRUARY 2004
[23]P. Hayton, “Analysis of Contrast Enhanced Breast MR Images,” DPhil. dissertation, Engineering Science, Oxford Univ., Oxford, U.K., 1998.
[24]Y. Kita, R. P. Highnam, and M. Brady, “Correspondence between different view breast X rays using curved epipolar lines,” Comput. Vis. Image Understand, vol. 83, pp. 38-55, 2001.
[25]Y. Kita, E. Tohno, R. P. Highnam, and M. Nrady, “A CAD system for the 3D location of lesions in mammograms,” Medical Image Analysis, vol. 6, pp. 267-273, 2002.
[26]Holland, John H., Adaptation in natural and Artificial System., Ann Arbor: University of Michigan Press, 1975.
[27]Bauer, R. J. and G. E. Liepins,(1988),”Genetic Algorithms and Computerized Trading Strategies , ” Working Paper, the Business School of Western Ontario University.
[28]Booker, L.,(1987), “Improving Search in Genetic algorithms,” in Davis, L.(Editor), Genetic Algorithms and Simulated Annealing.
[29]Goldberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning., Addison-Wesley, Reading MA, 1989.
[30]R. Highnam and M. Brady, Mammographic Image Analysis. Dordrecht, The Netherlands: Kluwer Academic, 1999.
[31]M. Yam, R. P. Highnam, J. M. Brady, and R. English, “Detecting calcifications using the hint representation,” in Proc. Computer Assisted Radiology and Surgery, 1999, pp. 373–377.
[32]R. Highnam and M. Brady, “X-ray image processing,” GB9 904 692.2, 1999.
[33]何典恭，線性代數，新文京開發出版，2003年。