臺灣博碩士論文加值系統

論文提出一個以類免疫演算法為基礎的多門控心室功能攝影影像切割與心室功能評估的系統，應用此影像處理技術於多門控心室功能影像的心室輪廓切割上，透過對一系列收縮舒張過程的心室影像進行輪廓切割，取得心室的輪廓區域範圍，以輔助醫師進行心臟功能的評估計算，以利醫師能夠提早並且準確地發現異常。本研究中利用了類免疫演算法來對抗雜訊較多且區域分別較不明確的多門控心室功能影像，並結合各種影像的前處理過程，透過類免疫的演化迭代，切割出心室區域輪廓，再透過對其Ejection Fraction的計算，並與現行使用的軟體所產生的數據做比對，期望能夠透過本研究的方法來取得一個較準確的心室輪廓與Ejection Fraction數值，進而達到輔助醫師做心臟機能判斷的最終目的。

In this thesis, we propose an artificial immune algorithm based image segmentation method for multigated ventriculography. The main purpose of this thesis is to develop a computerized system which helps physicians and radiologists to automatically predict the presence of heart disease as early as possible. We first segment and reconstruct the contour of left ventricular from the multigated ventriculography images. The evolution algorithm and active contour model are used to segment the contour accurately in this step. The segmented contour is then used to evaluate the Ejection Fraction parameters for the assessment of cardiac function. Experimental results show that the proposed method can provide an effective segmentation results and assessment of cardiac function in multigated ventriculography. Therefore, we can make use of image information to assistant the diagnosis. Doctors can also use this 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 resources. Meanwhile, it can be further used as the computer aided diagnosis system (CAD) for differential diagnosis in the future.

書名頁 i
論文口試委員審定書 ii
授權書 iii
中文摘要 vii
英文摘要 viii
誌謝 ix
目錄 xi
表目錄 xiii
圖目錄 xiv
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 研究流程與架構 3
1.4 全文架構 4
第二章 文獻探討 5
2.1 切割演算法 5
2.2 基因演算法 7
2.2.1 基因演算法特性 8
2.2.2 基因演算法流程 9
2.3 類免疫演算法 12
2.3.1 類免疫演算法的特性 14
2.3.2 類免疫演算法的流程 15
2.4 多門控心室功能攝影(MUGA) 16
第三章 研究方法 18
3.1 影像前處理 18
3.2 基因輪廓切割演算法 22
3.3 強化型混合免疫基因演算法(Enhancement Hybrid Immune Genetic Algorithm, EHIGA) 24
3.4 EHIGA演算法流程 25
3.5 EHIGA演算法之特性 27
第四章 實驗結果 28
4.1 實驗樣本 28
4.2 評估指標介紹 29
4.3 開發與測試環境 30
4.4 實驗參數 30
4.5 實驗成果 30
第五章 結論 40
參考文獻 41

[1] 101年度衛生系列(一)統計資料:多重死因統計，行政院衛生署，2013。
[2] 劉仁賢，認識核子醫學，2002。
[3] M.A. Savelonas, D.K. Iakovidis, and D.E.Maroulis, “An LBP-Based Active Contour Algorithm for Unsupervised Texture Segmentation,” IEEE International Conference on Pattern Recognition, ICPR 2006, 20-24 Aug., 2006, Hong Kong, China, vol.2, pp.279-282.
[4] D. Marr, E. Hildreth, “Theory of Edge Detection,” in Proc. R. Soc. Lond. B, pp. 187-217, 1980.
[5] W.-Y. Ma, B. S. Manjunath, “EdgeFlow: A Technique for Boundary Detection and Image Segmentation,” IEEE Trans. Image Processing, vol. 9, no. 8, pp. 1375-1388, Aug. 2000.
[6] R. Deriche, “Using Canny's Criteria to Derive A Recursively Implemented Optimal Edge Detector,” Int. J. Comput. Vis., pp. 167-187, 1987.
[7] K. L. Chung, H. L. Huang, and H. I. Lu, “Efficient Region Segmentation on Compressed Gray Images Using Quadtree and Shading Representation,” Pattern Recognition, vol. 37, pp. 1591-1605, 2004.
[8] R. Adams, L. Bischof, “Seeded Region Growing,” IEEE Trans. Pattern Anal. Machine Intell., vol. 16, no. 6, pp. 641-647, June 1994.
[9] S. A. Hojjatoleslami, J. Kittler, “Region Growing: A New Approach,” IEEE Trans. Image Processing, vol. 7, pp. 1079-1084, 1998.
[10] O. Monga, “An Optimal Region Growing Algorithm for Image Segmentation,” Int. J. Pattern Recog. Artif. Intell., vol. 1, pp. 351-375, 1987.
[11] P. C. Chen, T. Pavlidis, “Segmentation by Texture Using A Co-occurrence Matrix and A Split-and-merge Algorithm,” Comput. Graphics Image Processing, vol. 10, pp. 172-182, 1979.
[12] S. Chen, W. Lin, and C. Chen, “Split-and-merge Image Segmentation Based on Localized Feature Analysis and Statistical Tests,” CVGIP: Graph. Models Image Process, vol. 53, pp. 457-475, 1991.
[13] R. M. Haralick, L. G. Shapiro, “Survey: Image Segmentation Techniques,” Comput. Vis. Graph. Image Process., vol. 29, pp. 100-132, 1985.
[14] John Holland, “Adaptation in Natural and Artificial Systems,” University of Michigan Press, Ann Arbor, 1975.
[15] 施雅月，「智慧型決策」，交通大學資訊管理所博士班，2003。
[16] C. X Wang, et al, “A Novel Genetic Algorithm Based on Gene Therapy Theory,” Transactions of the Institute of Measurement and Control, vol. 28, pp. 253-262, 2006.
[17] 洪櫻慈，「基因演算法在向量量化之應用」，碩士論文，樹德科技大學，2005。
[18] 郭宏傑，「最大利潤機組排程與風險分析之研究」，碩士論文，中山大學，2010。
[19] 朱瑞興，「可拓人工免疫系統應用於多頻譜影像之研究」，碩士論文，國立勤益科技大學，2010。
[20] 郭宏傑，「最大利潤機組排程與風險分析之研究」，碩士論文，中山大學，2010。
[21] Lucia Ballerini, “Genetic Snakes for Medical Images Segmentation,” EvoIASP’ 99, LNCS 1596, pp. 59-73, 1999.
[22] 江潤成，「印刷電路板測試點選取最適化之研究」，碩士論文，元智大學，2011。
[23] 翁耀臨，「淺談迴歸分析與相關分析」，長榮大學。