跳到主要內容

臺灣博碩士論文加值系統

(44.192.38.248) 您好!臺灣時間:2022/11/27 07:02
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:江艾珊
研究生(外文):Ai-Shan Chiang
論文名稱:間接性螢光抗核抗體顯影之自動檢測技術
論文名稱(外文):Automatic Detection and Classification of Antinuclear Autoantibodies Cells in Indirect Immunofluorescence Images
指導教授:黃育仁黃育仁引用關係
指導教授(外文):Yu-Len Huang
口試委員:江季翰詹永寬黃育仁
口試委員(外文):Ji-Han JiangYung-Kuan ChanYu-Len Huang
學位類別:碩士
校院名稱:東海大學
系所名稱:資訊工程學系
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:2010
畢業學年度:98
語文別:英文
論文頁數:34
中文關鍵詞:間接性螢光切片抗核抗體組織性自我免疫細胞偵測影像分類
外文關鍵詞:indirect immunofluorescence patternantinuclear autoantibodiessystemic autoimmune diseasescell detectionimage classification
相關次數:
  • 被引用被引用:0
  • 點閱點閱:168
  • 評分評分:
  • 下載下載:21
  • 收藏至我的研究室書目清單書目收藏:0
在組織性自我免疫的疾病中,目前最受大家推薦用來檢測抗核抗體(antinuclear autoantibody, ANA)的方法是利用HEp-2的間接性螢光切片進行檢查。而此動作需要檢驗人員透過顯微鏡觀察細胞切片的形狀,才能夠進行完整且詳盡的定義。然而,因為缺乏自動化的檢驗流程及標準化的作業程序,此一檢驗過程仍然需要在專業且具有相當經驗的醫師或技術人員的指導下,才能獲得精確的診斷結果。因此在這樣的環境下,本論文的研究目的在於提出一個針對ANA進行自動檢驗的系統。此系統可以分為兩大部分,包含細胞偵測與影像分類。研究的第一部分是在間接性螢光切片的影像中,自動偵測出螢光性樣本中各細胞的邊緣與外型,並且利用針對圓進行霍夫轉換的技術,對於系統所找到的細胞進行初步的判斷。研究的另一個部分則是利用影像中的各個特徵,結合決策樹的方法對於影像進行分類。本論文針對六種抗核抗體類型的影像進行研究,而研究結果證明此方法提供一個穩定且快速的系統用於間接抗體螢光染色HEp-2細胞的偵測與分類。

Indirect immunofluorescence (IIF) with HEp-2 cells presents the major screening method for detection of antinuclear autoantibodies (ANA) in systemic autoimmune diseases. The identification of patterns has recently by a human inspecting the slides with a microscope. However, due to lacking in satisfied automation of inspection and a low level of standardization, this procedure still need highly specialized and experienced technician/physician to obtain diagnostic result. For this purpose, the aim of this paper is for developing an automatic inspection system that can be divided into HEp-2 cell detection and fluorescence pattern classification in ANA testing. The first part of this study is an automatic detection scheme to sketch outlines of fluorescence cells for HEp-2 cell detection in the IIF images by using the circular Hough transform (CHT). The second part of the system uses a decision tree for image classification of fluorescence pattern by using ANA characteristics. This study evaluates cells with six distinct fluorescence patterns from ANA images. The simulation results show that the proposed method provides a robust and fast automatic detection and classification of HEp-2 fluorescent patterns in ANA testing.
摘要
ABSTRACT
INDEX
LIST OF TABLES
LIST OF FIGURES
CHAPTER1 INTRODUCTION
CHAPTER2 CELL DETECTION
2.1 DATA ACQUISITION
2.2 AUTOANTIBODY FLUORESCENCE PATTERNS
2.3 AUTOMATIC DETECTION
2.4 PREPROCESSING OF THE PROPOSED METHOD
2.5 EULER NUMBER
2.6 CIRCULAR HOUGH TRANSFORM (CHT)
2.7 RESULT
CHAPTER3 IMAGE CLASSIFICATION
3.1 FEATURE EXTRACTION 200
3. 2 PATTERN CLASSIFICATION
3.3 RESULT
CHAPTER4 CONCLUSION
REFERENCE
[1] Y. Polotsky, J. P. Nataro, D. Kotler, T. J. Barrett, and J. M. Orenstein, "HEp-2 cell adherence patterns, serotyping, and DNA analysis of Escherichia coli isolates from eight patients with AIDS and chronic diarrhea," Journal of Clinical Microbiology, vol. 35, no. 8, pp. 1952-1958, Aug.1997.
[2] P. Soda, "Early Experiences in the Staining Pattern Classification of HEp-2 Slides," in Computer-Based Medical Systems 2007. CBMS '07. Twentieth IEEE International Symposium on, 2007, pp. 219-224.
[3] P. Soda and G. Iannello, "A Hybrid Multi-Expert Systems for HEp-2 Staining Pattern Classification," in Image Analysis and Processing 2007, pp. 685-690.
[4] H. S. Wu and J. Barba, "An Efficient Semiautomatic Algorithm for Cell Contour Extraction," Journal of Microscopy-Oxford, vol. 179, pp. 270-276, Sept.1995.
[5] H. S. Wu, J. Barba, and J. Gil, "Iterative thresholding for segmentation of cells from noisy images," Journal of Microscopy-Oxford, vol. 197, pp. 296-304, Mar.2000.
[6] H. S. Wu, J. Barba, and J. Gil, "An iterative algorithm for cell segmentation using short-time Fourier transform," Journal of Microscopy-Oxford, vol. 184, pp. 127-132, Nov.1996.
[7] Y.L.Huang, Y.L.Jao, T.Y.Hsieh, and C.W.Chung, "Adaptive Automatic Segmentation of HEp-2 Cells in Indirect Immunofluorescence Images," in Sensor Networks, Ubiquitous and Trustworthy Computing 2008, pp. 418-422.
[8] Y.L.Huang, C.W.Chung, T.Y.Hsieh, and Y.L.Jao, "Outline Detection for the HEp-2 Cell in Indirect immunofluorescence Images Using Watershed Segmentation," in Sensor Networks, Ubiquitous and Trustworthy Computing 2008, pp. 423-427.
[9] W. Hai-Shan, J. Barba, and J. Gil, "A parametric fitting algorithm for segmentation of cell images," Biomedical Engineering, vol. 45, no. 3, pp. 400-407, 1998.
[10] W. N. Lie, "Automatic Target Segmentation by Locally Adaptive Image Thresholding," Image Processing, vol. 4, no. 7, pp. 1036-1041, July1995.
[11] Y. H. Kim and S. D. Kim, "Image Flow Segmentation and Estimation Using Displaced Spatial Gradient," Electronics Letters, vol. 28, no. 24, pp. 2213-2215, Nov.1992.
[12] S. Sarkar and K. L. Boyer, "On Optimal Infinite Impulse-Response Edge-Detection Filters," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 11, pp. 1154-1171, Nov.1991.
[13] D. Hahm and U. Anderer, "Establishment of HEp-2 cell preparation for automated analysis of ANA fluorescence pattern," Cytometry Part A, vol. 69A, no. 3, pp. 178-181, Mar.2006.
[14] D. H. Solomon, A. J. Kavanaugh, and P. H. Schur, "Evidence-based guidelines for the use of immunologic tests: Antinuclear antibody testing," Arthritis & Rheumatism-Arthritis Care & Research, vol. 47, no. 4, pp. 434-444, Aug.2002.
[15] A. Rigon, P. Soda, D. Zennaro, G. Iannello, and A. Afeltra, "Indirect inununofluorescence in autoimmune diseases: Assessment of digital images for diagnostic purpose," Cytometry Part B-Clinical Cytometry, vol. 72B, no. 6, pp. 472-477, Nov.2007.
[16] U. Sack, S. Knoechner, H. Warschkau, U. Pigla, F. Emmrich, and M. Kamprad, "Computer-assisted classification of HEp-2 immunofluorescence patterns in autoimmune diagnostics," Autoimmunity Reviews, vol. 2, no. 5, pp. 298-304, Sept.2003.
[17] L. Vincent and P. Soille, "Watersheds in Digital Spaces - An Efficient Algorithm Based on Immersion Simulations," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, no. 6, pp. 583-598, June1991.
[18] S. Suhaila and T. Shimamura, "Power Spectrum tstimation Method for Image Denoising by Frequency Domain Wiener Filter,", 3 ed 2010, pp. 608-612.
[19] N. Otsu, "Threshold Selection Method from Gray-Level Histograms," IEEE Transactions on Systems Man and Cybernetics, vol. 9, no. 1, pp. 62-66, 1979.
[20] X.Lin, J.Ji, and Y.Gu, "The Euler Number Study of Image and its Application," in Industrial Electronics and Applications 2007, pp. 910-912.
[21] T. J. Atherton and D. J. Kerbyson, "Circle detection using Hough transform filters," in Image Processing and its Applications 1995, pp. 370-374.
[22] L. Hoo Cheol, C. Yungeun, K. Young Joong, H. Dae Hie, P. Sin Suk, and L. Myo Taeg, "Vision-Based Estimation of Bolt-Hole Location using Circular Hough transform," 2009, pp. 4821-4826.
[23] P. Perner, "Classification of HEp-2 Cells using Fluorescent Image Analysis and Data Mining," in Pattern Recognition, 2 ed 1998, pp. 1677-1679.
[24] P. Sreedevi, W. L. Hwang, and S. Lei, "An Examplar-Based Approach for Texture Compaction Synthesis and Retrieval," IEEE Transactions on Image Processing, vol. 19, no. 5, pp. 1307-1318, May2010.
[25] Y. Zhengmao, H. Mohamadian, and I. Majlesein, "Adaptive Enhancement of Gray Level and True Color Images with Quantitative Measurement Using Entropy and Relative Entropy," 2008, pp. 127-131.
[26] K. Shah and V. Gandhi, "Image Classification Based on Textural Features using Artificial Neural Network (ANN)," 2004.
[27] A. Abdelhalim and I. Traore, "A New Method for Learning Decision Trees from Rules," 2009, pp. 693-698.
[28] M. Moussa, J. Ruwanpura, and G. Jergeas, "Decision tree modeling using integrated multilevel stochastic networks," Journal of Construction Engineering and Management-Asce, vol. 132, no. 12, pp. 1254-1266, Dec.2006.
[29] M. Moussa, J. Y. Ruwanpura, and G. Jergeas, "Decision tree module within decision support simulation system," 2004, pp. 1268-1276.
[30] D. Haizhou and M. Chong, "Study on constructing generalized decision tree by using DNA coding geneticalgorithm," 2009, pp. 163-167.


連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top