臺灣博碩士論文加值系統

激發光-螢光矩陣光譜為非侵入式組織檢測，且在臨床上越來越受重視，然
而，激發光-螢光矩陣光譜的內在特徵至今仍不清楚。光漂白特性與化學物質的
複雜組成份，造成不同物質的螢光光譜常有重疊干擾導致不易辨識。過去有許多
研究將主成分分析法用於激發光-螢光矩陣分析，以提取光譜中之特徵，並檢測
這些特徵與疾病的關聯性，但不同組織成分的光譜特徵並沒有被完全地分開或清
楚地定義。多維整體經驗模態分析法為近年來新提出的方法，此方法透過反覆減
去局部均值以對資料進行解構，可提取在多維空間尺度下的震盪且不會產生訊息
缺失。本研究的目的是利用多維整體經驗模態分析法提取激發光-螢光矩陣光譜
的內在特徵。我們先用模擬的訊號來檢視分析方法對與發光-螢光矩陣光譜相似
但較為單純的訊號的解構能力，之後再以此分析方法進行發光-螢光矩陣光譜之
解構。本研究亦使用主成分分析法與多維整體經驗模態分析法做比較。結果顯示，
主成分分析可呈現出與化學物相關的主要光譜特徵（以膠原蛋白為主），而多維
整體經驗模態分析法可進一步呈現光譜中各種螢光物質的獨立特徵，例如膠原蛋
白、為生素 D 等。整體而言，多維整體經驗模態分析法提供一個光譜分析的新觀
點，可提取光譜中螢光特徵，並增進生物螢光檢測的可能性。

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method decomposes data by subtracting local means iteratively and can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to extract the intrinsic characteristics of EEM by using MEEMD. We use simulated signal to examine the decomposition ability of MEEMD on decomposing signal which was similar to EEM but simpler than EEM, and then MEEMD was applied to decompose EEM. PCA was used to compare with MEEMD in this study. The results indicate that although PCA provides the main spectral features associated with chemical compounds, which mainly contributed by collagen, MEEMD can provide additional intrinsic features with more reliable mapping of individual chemical compounds, e.g. collagen and vitamin D. Overall, MEEMD provide a new point of view on EEM analysis and has the potential to extract intrinsic fluorescence features and improve the detection of biological fluorophores.of individual chemical compounds, e.g. collagen and vitamin D. Overall, MEEMD provide a new point of view on EEM analysis and has the potential to extract intrinsic
fluorescence features and improve the detection of biological fluorophores.

Contents
摘要 i
Abstract ii
致謝 iii
Contents iv
Lists of figures vi
Lists of tables viii
1. Introduction 1
1.1. Background 1
1.1.1. Optical spectroscopy 1
1.1.2. Fluorescence spectroscopy in biomedical research 1
1.2. Motivation 3
1.3. Literature review 4
1.3.1. Spectroscopic property 4
1.3.2. Fluorescence spectroscopy analysis 5
1.3.3. Introduction to principal component analysis (PCA) 6
1.3.4. Limitation of PCA 7
1.3.5. Empirical mode decomposition (EMD) &; Multi-dimensional empirical mode decomposition (MEEMD) 8
1.4. Objective 11
2. Material and Method 12
2.1. Procedure 12
2.2. Data 14
2.2.1. Data simulation 14
2.2.2. Optical experiment 14
2.3. Analysis 17
2.3.1. EEM preprocessing 17
2.3.2. Multi-dimensional ensemble empirical mode decomposition 18
2.3.3. Principal component analysis 19
2.4. Recognition 21
3. Results 22
3.1. Decomposition results of EEM 22
3.1.1. BIMFs 22
3.1.2. PCs 23
3.2. Decomposition results of EEM 25
3.2.1. BIMFs 25
3.2.2. PCs 26
4. Discussion 28
4.1. Discussion of simulated data 28
4.1.1. Extracted features of simulated data 28
4.1.2. Properties of decomposition results 30
4.1.3. Decomposition performance of MEEMD and PCA 30
4.2. Extracted features of EEM 32
4.2.1. Features in BIMFs and its related biological fluorophores 32
4.2.2. Features in PCs and its related biological fluorophores 33
4.3. Decomposition properties of MEEMD and PCA 35
4.3.1. Unfold direction of PCA 35
4.3.2. Starting direction of MEEMD 35
4.4. Features of PCs and BIMFs 37
4.4.1. Orthogonality of decomposition results 37
4.4.2. Comparison of features in PCs and BIMFs 37
4.5. Relation between decomposition results and storage time 41
4.5.1. Relation between PCs and storage time 41
4.5.2. Relation between BIMFs and storage time 44
5. Conclusion 46
6. Future work 47
Reference 49

[1] K. Vishwanath and N. Ramanujam, "Fluorescence spectroscopy in vivo," in Encyclopedia of analytical chemistry, R. A. meyers, Ed., ed, 2000.
[2] I. J. Bigio and S. G. Bown, "Spectrroscopic sensing of cancer and cancer therapy: Current status of translational research," Cancer biology &; therapy, vol. 3, pp. 259-267, 2004.
[3] Y. S. Fu, "Pathology of cervical carcinoma," in Gynecology and Obstetrics. vol. 4, J. J. Sciarra, Ed., Cdr ed: Lippincott Williams &; Wilkins, 2004.
[4] E. Dufour, J. P. Frencia, and E. Kane, "Development of a rapid method based on front-face fluorescence spectroscopy for the monitoring of fish freshness," Food Research International, vol. 36, pp. 415-423, 2003.
[5] C. M. Andersen and J. P. Wold, "Fluorescence of muscle and connective tissue from cod and salmon," Journal of Agricultural and Food Chemistry, vol. 51, pp. 470-476, 2003.
[6] N. Ramanujam, "Fluorescence spectroscopy of neoplastic and non-neoplastic tissues," Neoplasia (New York, NY), vol. 2, p. 89, 2000.
[7] E. Dufour, A. Letort, A. Laguet, A. Lebecque, and J. N. Serra, "Investigation of variety, typicality and vintage of French and German wines using front-face fluorescence spectroscopy," Analytica Chimica Acta, vol. 563, pp. 292-299, 2006.
[8] C. Zhu, E. S. Burnside, G. A. Sisney, L. R. Salkowski, J. M. Harter, B. Yu, et al., "Fluorescence spectroscopy: An adjunct diagnostic tool to image-guided core needle biopsy of the breast," IEEE Transactions on Biomedical Engineering, vol. 56, pp. 2518-2528, 2009.
[9] R. Richards-Kortum and E. Sevick-Muraca, "Quantitative optical spectroscopy for tissue diagnosis," Annual review of physical chemistry, vol. 47, pp. 555-606, 1996.
[10] A. Katz and R. Alfano, "Optical biopsy-detecting cancer with light," in Biomedical Optical Spectroscopy and Diagnostics, 1996, p. FT1.
[11] V. Betz, H. Schneckenburger, H. Alleroeder, G. W. Sybrecht, and J.-U. Meyer, "Evaluation of changes in the NADH level between carcinogenic and normal tissue samples by use of fluorescence spectroscopy," International Symposium on Biomedical Optics Europe'94, pp. 284-291, 1995.
[12] R. Karoui, E. Thomas, and E. Dufour, "Utilisation of a rapid technique based on front-face fluorescence spectroscopy for differentiating between fresh and frozen–thawed fish fillets," Food Research International, vol. 39, pp. 349-355, 2006.
[13] L. Panasyuk. (2009). Does tissue fluorese? Available: http://panaworks.com/lana/tissue/fluorescence.htm
[14] N. Ramanujam, M. F. Mitchell, A. Mahadevan, S. Warren, S. Thomsen, E. Silva, et al., "In-vivo diagnosis of cervical intraepithelial neoplasia using 337-nm-excited laser-induced fluorescence," Proceedings of the National Academy of Sciences of the United States of America, vol. 91, pp. 10193-10197, 1994.
[15] R. M. Cothren, M. V. Sivak Jr, J. Van Dam, R. E. Petras, M. Fitzmaurice, J. M. Crawford, et al., "Detection of dysplasia at colonoscopy using laser-induced fluorescence: a blinded study," Gastrointestinal Endoscopy, vol. 44, pp. 168-176, 1996.
[16] R. A. Schwarz, W. Gao, C. R. Weber, C. Kurachi, J. J. Lee, A. K. El-Naggar, et al., "Noninvasive evaluation of oral lesions using depth-sensitive optical spectroscopy," Cancer, vol. 115, pp. 1669-1679, 2009.
[17] I. Georgakoudi, B. C. Jacobson, M. G. Muller, E. E. Sheets, K. Badizadegan, D. L. Carr-Locke, et al., "NAD(P)H and collagen as in vivo quantitative fluorescent biomarkers of epithelial precancerous changes," Cancer Research, vol. 62, pp. 682-687, 2002.
[18] G. M. Palmer, C. F. Zhu, T. M. Breslin, F. S. Xu, K. W. Gilchrist, and N. Ramanujam, "Comparison of multiexcitation fluorescence and diffuse reflectance spectroscopy for the diagnosis of breast cancer (March 2003)," IEEE Transactions on Biomedical Engineering, vol. 50, pp. 1233-1242, 2003.
[19] S. K. Chang, Y. N. Mirabal, E. N. Atkinson, D. Cox, A. Malpica, M. Follen, et al., "Combined reflectance and fluorescence spectroscopy for in vivo detection of cervical pre-cancer," Journal of biomedical optics, vol. 10, pp. 024031-02403111, 2005.
[20] S. C. Chu, T. C. R. Hsiao, J. K. Lin, C. Y. Wang, and H. K. Chiang, "Comparison of the performance of linear multivariate analysis methods for normal and dyplasia tissues differentiation using autofluorescence spectroscopy," IEEE Transactions on Biomedical Engineering, vol. 53, pp. 2265-2273, 2006.
[21] L. Liu, Y. Nie, L. Lin, W. Li, Z. Huang, S. Xie, et al., "Pattern recognition of multiple excitation autofluorescence spectra for colon tissue classification," Photodiagnosis and Photodynamic Therapy, vol. 10, pp. 111-119, 2012.
[22] H. Abdi and L. J. Williams, "Principal component analysis," Wiley Interdisciplinary Reviews: Computational Statistics, vol. 2, pp. 433-459, 2010.
[23] N. Lastein. Principal component analysis (PCA). Available: http://models.life.ku.dk/~movies/KVL_PCA.wmv
[24] J. Shlens, "A tutorial on principal component analysis," Systems Neurobiology Laboratory, University of California at San Diego, 2005.
[25] N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, et al., "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, vol. 454, pp. 903-995, 1998.
[26] Z. Wu and N. E. Huang, "Ensemble empirical mode decomposition: a noise-assisted data analysis method," Advances in Adaptive Data Analysis, vol. 1, pp. 1-41, 2009.
[27] Z. Wu, N. E. Huang, and X. Chen, "The multi-dimensional ensemble empirical mode decomposition method," Advances in Adaptive Data Analysis, Theory and Applications, vol. 1, pp. 339-372, 2009.
[28] C. W. Wu, T. C. Hsiao, S. C. Chu, H. H. Hu, and J. C. Chen, "Fibre optic fluorescence spectroscopy for monitoring fish freshness," Proceedings of the SPIE - The International Society for Optical Engineering, vol. 8220, p. 82200H, 2012.
[29] C. W. Wu, "Evaluation index for fish freshness based on EEM analysis," Master, Institute of Biomedical Engineering, National Chiao Tung University, Hsinchu, Taiwan, 2012.
[30] 楊純明 and 李裕娟, "從植物之光週期看發光二極體在農業生產上之應用潛力," 2009.
[31] Y. Taniyasu, M. Kasu, and T. Makimoto, "An aluminium nitride light-emitting diode with a wavelength of 210 nanometres," Nature, vol. 441, pp. 325-328, 2006.