博碩士論文 962406014 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:11 、訪客IP:18.226.251.68
姓名 謝耀方(Yao-Fang Hsieh)  查詢紙本館藏   畢業系所 光電科學與工程學系
論文名稱 嵌入式繼光鏡顯微超頻譜影像系統應用在口腔癌切片及活體之設計及研究
(Research and Design of Finite Conjugate Embedded Relay Lens Microscopic Hyperspectral Imaging System (ERL-MHIS) on Oral Cancer in-vitro and in-vivo Application)
相關論文
★ 半導體雷射控制頻率★ 比較全反射受挫法與反射式干涉光譜法在生物感測上之應用
★ 193nm深紫外光學薄膜之研究★ 超晶格結構之硬膜研究
★ 交錯傾斜微結構薄膜在深紫外光區之研究★ 膜堆光學導納量測儀
★ 紅外光學薄膜之研究★ 成對表面電漿波生物感知器應用在去氧核糖核酸及微型核糖核酸 雜交反應檢測
★ 成對表面電漿波生物感測器之研究及其在生醫上的應用★ 探討硫化鎘緩衝層之離子擴散處理對CIGS薄膜元件效率影響
★ 以反應性射頻磁控濺鍍搭配HMDSO電漿聚合鍍製氧化矽摻碳薄膜阻障層之研究★ 掃描式白光干涉儀應用在量測薄膜之光學常數
★ 量子點窄帶濾光片★ 以量測反射係術探測光學薄膜之特性
★ 軟性電子阻水氣膜之有機層組成研究★ 利用介電質-金屬對稱膜堆設計雙曲超穎材料並分析其光學特性
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 口腔癌的五年存活率約57%,若能早期發現,則能提升到80%左右。目前診斷口腔癌的方式仍以切片為主,但切片的判斷會有人為經驗上的誤差,因此病理醫生希望能找出量化診斷的儀器來輔助診斷口腔癌。由於顯微超頻譜影像系統能同時提供切片的組織形態資訊以及光譜資訊,近來被使用在in-vitro口腔癌的檢測,但因其掃描結構複雜且高倍率影像品質不佳,影響診斷準確率。因此本研究發展一套嵌入式繼光鏡超頻譜影像系統,並將其結合顯微鏡成為嵌入式繼光鏡顯微超頻譜影像系統,利用繼光鏡的遠心特性,將本來在顯微鏡物平面的掃描機制轉移到像平面,使用繼光鏡來掃描影像,如此掃描解析度不用隨著放大倍率而改變,不僅增加掃描時的穩定性且將掃描結構簡化。並使用20個老鼠切片來做初步的儀器驗證,得到靈敏度88.9%及特異度87.6%。此外,分別使用雞尾酒方法與組織分層法診斷29個及34個人類病理切片,來驗證這套系統的臨床適用性,前者得到靈敏度90%及特異度87.8%,後者得到靈敏度94.12%及特異度91.18%。最後,本研究也將此系統結合光纖內視鏡,做初步的臨床in-vivo實驗。
摘要(英) The 5-years survival rate of oral cancer is approximately 57%; however, if the oral cancer is discovered in the early stage, the 5-years survival rates can be increased to 80%. Biopsy is a conventional approach for diagnosing oral cancer. In addition to allow pathologists to diagnose the stage of cancer accurately, a biopsy also allows them to prescribe the most appropriate treatment. However, the difference in experience and subjectivity between pathologists might affect their diagnostic accuracy. Therefore, the pathologist hopes to find an approach to quantitatively diagnose oral cancer.
A microscopic hyperspectral imaging system (MHIS), which can simultaneously present the tissue image and the spectral information of each pixel on an image, has been developed to aid physician to quantitatively diagnose oral cancer. However, the MHIS has some hardware issues, such as the unstable scanning mechanism, complex mechanical structure, and inconvenient alignment. Hence, this study develops a novel embedded relay lens microscopic hyperspectral imaging system (ERL-MHIS), which is composed of the proposed ERL-HIS and a microscope, to improve the hardware issues by optical transferring the scanning plane from objective plane to imaging plane.
In this study, the development of the ERL-MHIS is discussed and the capability of the system is firstly demonstrated by diagnosing early stage oral cancer of twenty mice biopsies. The sensitivity and specificity are 88.9% and 87.6%, respectively. Then, twenty-nine oral cancer (fourteen in early stage) patient’s biopsies are diagnosed using cocktail approach, which diagnoses the biopsy according to the patient’s condition. The sensitivity and specificity are 90% and 87.8%, respectively. Finally, the tissue stratification approach, which combines the morphological and spectral information of biopsy to discriminate cancer form normal biopsies, is used to diagnose thirty-four patient’s biopsies. The sensitivity and specificity are 94.12% and 91.18%, respectively. Moreover, we also connect the ERL-HIS with the fiberscope for in-vivo diagnosis.
關鍵字(中) ★ 超頻譜
★ 顯微鏡
★ 癌症
★ 切片
★ 活體
關鍵字(英) ★ Hyperspectral
★ Microscopy
★ Cancer
★ Biopsy
★ in-vivo
論文目次 中文摘要 I
Abstract II
Acknowledgements III
Contents IV
List of Figures VII
List of Tables XI
Chapter 1. Introduction 1
Chapter 2. Spectroscopy 4
2-1 Introduction of spectroscopy…………………………………………………………….15
2-2 Classification of spectroscopy by the interaction between radiation and substance ..……5
2-2-1 Absorption spectroscopy………………………………..…………………………5
2-2-2 Emission spectroscopy………………………………………………………..…...6
2-2-3 Scattering spectroscopy……..……………………………………………………..9
Chapter 3. Fundamentals of light-matter interactions ….12
3-1 Interactions between light and molecule………………………………………………...12
3-2 Interactions between light and cells……………………………………………………..13
3-3 Interactions between light and bulk matter……………………………………………...15
3-4 Interactions between light and tissues…………………………………………………...16
Chapter 4. Optical imaging modalities for biomedical applications 19
4-1 Optical imaging modalities classified to absorption spectroscopy……………………...19
4-1-1 Transmission microscopy………………………………………………………...19
4-2 Optical imaging modalities classified to scattering spectroscopy………………………21
4-2-1 Optical coherence tomography (OCT)…………………………………………...21
4-2-2 Confocal microscopy…………………………………………………………….23
4-2-3 Coherent anti-stokes Raman scattering (CARS)…………………………………24
4-3 Optical imaging modalities classified to emission spectroscopy……………………….25
4-3-1 Multiphoton microscopy…………………………………………………………25
4-3-2 Fluorescence lifetime imaging microscopy (FLIM)……………………………..27
4-3-3 Multispectral image………………………………………………………………29
4-3-4 Hyperspectral image……………………………………………………………...30
Chapter 5. The proposed novel hyperspectral imaging systems 36
5-1 Introduction of proposed in-vitro and in-vivo hyperspectral imaging systems………….36
5-2 Disadvantages of conventional microscopic hyperspectral system……………………..36
5-3 Finite conjugate relay lens………………………………………………………………39
5-3-1 Design principle………………………………………………………………….39
5-3-2 Simulations of relay lens…………………………………………………………40
5-3-3 Experiments of relay lens………………………………………………………...43
5-4 Embedded Relay Lens Microscopic Hyperspectral Imaging System (ERL-MHIS)……45
5-4-1 Operational principle of ERL-HIS……………………………………………….45
5-4-2 Operational Principle of ERL-MHIS…………………………………………….47
5-4-3 Analysis and calibration of ERL-MHIS………………………………………….51
5-4-4 Experiments and results of ERL-MHIS………………………………………….52
5-5 Embedded Relay Lens Fiberscopic Hyperspectral Imaging System (ERL-FHIS) ……...56
Chapter 6. ERL-MHIS for in-vitro oral cancer examination 59
6-1 Introduction of oral cancer………………………………………………………………60
6-2 Mice oral cancer biopsy examination…………………………………………………...61
6-2-1 Biopsy preparation and data collection…………………………………………..61
6-2-2 Data processing and analytical methods…………………………………………63
6-2-3 Results and discussion……………………………………………………………65
6-3 Human oral cancer biopsy examination by cocktail approach………………………….70
6-3-1 Patient biopsy preparation………………………………………………………..70
6-3-2 Five spectral methods for diagnosing oral cancer………………………………..73
6-3-3 Cocktail approach………………………………………………………………...75
6-3-4 Results and discussions…………………………………………………………..76
6-4 Human oral cancer biopsy examination by tissue classification………………………..81
6-4-1 Patient biopsy and image preparations…………………………………………...81
6-4-2 Cell classification on spectral domain……………………………………………82
6-4-3 Tissue stratification analysis on spatial domain………………………………….86
6-4-4 Results and discussions………………………………..………………………....92
Chapter 7. ERL-FHIS for in-vivo oral cancer examination 97
7-1 Patient samples preparations and image acquisition………………………………….....97
7-2 Data processing and analysis…………………………………………………………....97
7-3 Results and discussions………………………………………………………………..100
Chapter 8. Conclusions and future works 102
List of References 106
Personal publications 116
參考文獻 [1] D. Pavia, G. Lampman, G. Kriz, and J. Vyvyan, Introduction to Spectroscopy: Cengage Learning, 2008.
[2] G. M. Barrow, Introduction to Molecular Spectroscopy: McGraw-Hill, 1998.
[3] J. M. Hollas, Modern Spectroscopy: Wiley, 2004.
[4] B. W. Carroll, D. A. Ostlie, An Introduction to Modern Astrophysics: Addison-Wesley, 2006.
[5] K. S. Krane, Modern Physics: Wiley, 2012.
[6] A. N. Cox, Allen′s Astrophysical Quantities: Springer Science & Business Media, 2000.
[7] H. Yokoyama, and K. Ujihara, Spontaneous emission and laser oscillation in microcavities: CRC Press, 1995.
[8] A. F. van Driel, G. Allan, C. Delerue, P. Lodahl, W. L. Vos, and D. Vanmaekelbergh, “Frequency-Dependent Spontaneous Emission Rate from CdSe and CdTe Nanocrystals: Influence of Dark States,” Physical Review Letters, vol.95, pp.236804-236815, 2005
[9] J. M. Chalmers, and P. Griffiths, Handbook of Vibrational Spectroscopy: Wiley, 2002.
[10] R. Herrmann, “Quantities and units in clinical chemistry: Nebulizer and flame properties in flame emission and absorption spectrometry,” Pure and Applied Chemistry, vol. 58, pp.1737-1742, 1986.
[11] D. A. Skoog, F. J. Holler, and S, R. Crouch, Principles of Instrumental Analysis: Cengage Learning, 2006.
[12] P. N. Prasad, Introduction of Biophotonics: John Wiley & Sons, 2003.
[13] H. Lodish, A. Berk, S. L. Zipursky, P. Matsudaira, D. Baltimore, and J. Darnell, Molecule Cell Biology: W. H. Freeman, 2000.
[14] V. Tuchin, Tissue Optics: SPIE, 2007.
[15] Z. Chi, and S. A. Asher, “UV Raman determination of the environment and solvent exposure of Tyr and Trp residues,” Journal of Physical Chemistry B, vol. 102, pp. 9595-9602, 1998.
[16] N. B. Colthup, L. H. Daly, and S. E. Wiberley, Introduction to Infrared and Raman Spectroscopy: Academic Press, 1990.
[17] J. R. Lakowicz, Principals of Flouresence Spectometry: Kluwer/Plenum, 1999.
[18] O. Krichevskyl, and G. Bonnet, “Fluorescence correlation spectroscopy: the technique and its applications,” Reports on Progress in Physics, vol. 65, pp. 251-297, 2002.
[19] L. Wang, and T. Keiderling, “Vibrational circular dichroism studies of the A-to-B conformational transition in DNA,” Biochemistry, vol. 31, pp. 10265-10271, 1992.
[20] R. P. Feynman, The Feynman Lectures on Physics: Addison Wesley Longman, 1970.
[21] A. S. Glassner, An Introduction to Ray Tracing: Morgan Kaufmann, 1989.
[22] J. T. Houghton, The Physics of Atmospheres: CUP Archive, 1977.
[23] L. Rayleigh, “Investigations in optics, with special reference to the spectroscope,” Monthly Notices of the Royal Astronomical Society, vol. 40, pp. 254-267, 1880.
[24] D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science, vol. 254, pp.1178-1181, 1991.
[25] M. E. Brezinski, and J. G. Fujimoto , “Optical coherence tomography: high-resolution imaging in nontransparent tissue,” IEEE J. Selected Topics in Quantum Electronics, vol. 5, pp. 1185-1192, 1999.
[26] A. A. Michelson, “On the Correction of Optical Surfaces,” Proceedings of the National Academy of Sciences of the United States of America, vol. 4, pp. 210-212.
[27] M. Born, and E. Wolf, Principles of Optics, 7th Edition, Cambridge University Press: Cambridge, 1999.
[28] G. J. Brakenhoff, “Imaging modes of confocal scanning microscopy,” Journal of Microscopy, vol. 117, pp. 233-242, 1979.
[29] D. M. Shotton, “Confocal scanning optical microscopy and its applications for biological specimens,” Journal of Cell Science, vol. 94, pp. 175-206, 1989.
[30] J. X. Cheng, A. Volkmer, L. D. Book, and X. S. Xie, “An epi-detected coherent anti-stokes Raman scattering (E-CARS) microscope with high spectral resolution and high sensitivity,” Journal Physical Chemistry B, vol. 105, pp. 1277-1280, 2001.
[31] A. Diaspro, M. Corosu, P. Ramoino, and M. Robello, “Adapting a Compact Confocal Microscope System to a Two-Photon Excitation Fluorescence Imaging Architecture,” Microscopy Research and Technique, vol. 47, pp. 196-205, 1999.
[32] EM spectrum. (2013). Available: http://en.wikipedia.org/wiki/File:EM_spectrum.svg
[33] M. A. Afromowitz, “Multispectral imaging of burn wounds: a new clinical instrument for evaluating burn depth,” IEEE Transactions on Biomedical Engineering, vol. 35, pp. 842-850, 1988.
[34] A. J. Chaudhari, F. Darvas, J. R. Bading, R. A. Moats, P. S. Conti, D. J. Smith, S. R. Cherry, and R. M. Leahy, “Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging,” Physics in Medicine and Biology, vol .50, pp. 5421-5441, 2005.
[35] R.G. Roozbahani, M. H. Ghassemian, and A. R. Sharafat, “Estimating gain fields in multispectral MRI,” IEEE Transactions on Biomedical Engineering, vol. 47, pp. 1610-1615, 2000.
[36] P. Symvoulidis, H. Z. M. Perez, C. Cruz, M. Schwaiger, V. Ntziachristos, and G. G. Westmeyer, “Serial sectioning and multispectral imaging system for versatile biomedical applications,” IEEE 11th International Symposium on Biomedical Imaging (ISBI), vol. 2014, pp. 890-893, 2014.
[37] G. E. Carver, S. A. Locknar, W. A. Morrison, V. K. Ramanujan, and D. L. Farkas, “High-speed multispectral confocal biomedical imaging,” Journal of Biomedical Optics, vol. 19, pp. 36016, 2014.
[38] P. M. Lane, T. Gilhuly, P. Whitehead, H. Zeng, C. F. Poh, S. Ng, P. M. Williams, L. Zhang, M. P. Rosin, and C. E. MacAulay, “Simple device for the direct visualization of oral-cavity tissue fluorescence,” Journal of Biomedical Optics, vol. 11, pp. 024006, 2006.
[39] W. L. Curvers, R. Singh, L. M. Song, H. C. Wolfsen, K. Ragunath, K. Wang, M. B. Wallace, P. Fockens, and J. J. Bergman, “Endoscopic tri-modal imaging for detection of early neoplasia in Barrett′s oesophagus: a multi-centre feasibility study using high-resolution endoscopy, autofluorescence imaging and narrow band imaging incorporated in one endoscopy system,” Video Journal and Encyclopedia of GI Endoscopy, vol. 57, pp. 167-172, 2008.
[40] D. Roblyer, R. Richards-Kortum, K. Sokolov, A. K. El-Naggar, M. D. Williams, C. Kurachi, and A. M. Gillenwater, “Multispectral optical imaging device for in vivo detection of oral neoplasia,” Journal of Biomedical Optics, vol. 13, pp. 024019, 2008.
[41] D. Roblyer, C. Kurachi, V. Stepanek, R. A. Schwarz, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Comparison of multispectral wide-field optical imaging modalities to maximize image contrast for objective discrimination of oral neoplasia,” Journal of Biomedical Optics, vol. 15, pp. 066017, 2010.
[42] Y. Yang, X. Sha, and Z. H. Zhang, “Multispectral imaging system using Rotary polarization acousto-optic tunable filter,” IEEE 10th Russian-Chinese Symposium on Laser Physics and Laser Technologies (RCSLPLT) and 2010 Academic Symposium on Optoelectronics Technology (ASOT), vol. 2010, pp. 49-51, 2010.
[43] J. Y. Hardeberg, F. Schmitt, and H. Brettel, “Multispectral color image capture using a liquid crystal tunable filter,” Optical Engineering, vol. 41, pp. 2532-2548, 2002.
[44] A. F. H. Goetz, “Three decades of hyperspectral remote sensing of the Earth: a personal view,” Remote Sensing of Environment, vol. 113, pp. 5-16, 2009.
[45] C. Fischer and I. Kakoulli, “Multispectral and hyperspectral imaging technologies in conservation: current research and potential applications,” Reviews in Conservation, Vol. 7, pp. 3-16, 2006.
[46] H. Liang, “Advances in multispectral and hyperspectral imaging for archaeology and art conservation,” Journal of Applied Physics, vol. 106, pp. 309-323, 2012.
[47] M. Govender, K. Chetty, and H. Bulcock, “A review of hyperspectral remote sensing and its application in vegetation and water resource studies,” Water SA, vol. 33, pp. 145-151, 2007.
[48] E. Adam, O. Mutanga, and D. Rugege, “Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review,” Wetlands Ecology and Management, vol. 18, pp. 281-296, 2010.
[49] A. A. Gowen, C. P. O′Donnella, P. J. Cullenb, G. Downeyc, and J. M. Friasb “Hyperspectral imaging-an emerging process analytical tool for food quality and safety control,” Trends in Food Science & Technology, vol. 18, pp. 590-598, 2007.
[50] Y. Z. Feng and D. W. Sun, “Application of hyperspectral imaging in food safety inspection and control: a review,” Critical Reviews in Food Science and Nutrition, vol. 52, pp. 1039-1058, 2012.
[51] G. J. Edelman, E. Gastonb, T. G. van Leeuwena, P. J. Cullenc, and M. C. G. Aaldersa “Hyperspectral imaging for non-contact analysis of forensic traces,” Forensic Science International, vol. 223, pp. 28-39, 2012.
[52] D. B. Malkoff and W. R. Oliver, “Hyperspectral imaging applied to forensic medicine,” Proceeding of SPIE, vol. 3920, pp. 108-116, 2000.
[53] J. Kuula, I. Pölönen, H. H. Puupponen, T. Selander; T. Reinikainen, T. Kalenius, and H. Saari, “Using VIS/NIR and IR spectral cameras for detecting and separating crime scene details,” Proceeding of SPIE, vol. 8359, pp. 83590, 2012.
[54] R. L. Schuler, P. E. Kish, and C. A. Plese, “Preliminary observations on the ability of hyperspectral imaging to provide detection and visualization of bloodstain patterns on black fabrics,” Journal of Forensic Sciences, vol. 57, 1562-1569, 2012.
[55] O. Carrasco, R. B. Gomez, C. Arun, and W. E. Roper, “Hyperspectral imaging applied to medical diagnoses and food safety,” Proceeding of SPIE, vol. 5097, pp. 215-221, 2003.
[56] V. R. Kolli, A. R. Shaha, H. E. Savage, P. G. Sacks, M. A. Casale, and S. P. Schantz, “Native cellular fluorescence can identify changes in epithelial thickness in-vivo in the upper aerodigestive tract,” The American Journal of Surgery, vol. 170, pp. 495-498, 1995.
[57] J. K. Dhingra, D. F. Perrault, Jr, K. McMillan, and et al., “Early diagnosis of upper aerodigestive tract cancer by autofluorescence,” Archives of Otolaryngology–Head & Neck Surgery, vol. 122, pp. 1181-1186, 1996.
[58] D. R. Ingrams, J. K. Dhingra, K. Roy, D. F. Perrault, I. D. Bottrill, S. Kabani, E. E. Rebeiz, M. M. Pankratov, S. M. Shapshay, R. Manoharan, I. Itzkan, and M. S. Feld, “Autofluorescence characteristics of oral mucosa,” Head & Neck, vol. 19, pp. 27-32, 1997.
[59] G. A. Wagnieres, W. M. Star, and B. C. Wilson, “In vivo fluorescence spectroscopy and imaging for oncological applications,” Photochemistry and Photobiology, vol. 68, pp. 603-632, 1998.
[60] A. Gillenwater, R. Jacob, R. Ganeshappa, B. Kemp, A. K. El-Naggar, J. L. Palmer, G. Clayman, M. F. Mitchell, and R. Richards-Kortum, “Noninvasive diagnosis of oral neoplasia based on fluorescence spectroscopy and native tissue autofluorescence,” Archives of Otolaryngology-Head & Neck Surgery, vol. 124, pp. 1251-1258, 1998.
[61] S. P. Schantz, V. Kolli, H. E. Savage, G. P. Yu, J. P. Shah, D. E. Harris, A. Katz, R. R. Alfano, and A. G. Huvos, “In vivo native cellular fluorescence and histological characteristics of head and neck cancer,” Clinical Cancer Research, vol. 4, pp. 1177-1182, 1998.
[62] M. Inaguma and K. Hashimoto, “Porphyrin-like fluorescence in oral cancer - In vivo fluorescence spectral characterization of lesions by use of a near-ultraviolet excited autofluorescence diagnosis system and separation of fluorescent extracts by capillary electrophoresis,” Cancer, vol. 86, pp. 2201-2211, 1999.
[63] C. S. Betz, M. Mehlmann, K. Rick, H. Stepp, G. Grevers, R. Baumgartner, and A. Leunig A, “Autofluorescence imaging and spectroscopy of normal and malignant mucosa in patients with head and neck cancer,” Lasers in Surgery and Medicine, vol. 25, pp. 323–334, 1999.
[64] N. Ramanujam, “Fluorescence spectroscopy of neoplastic and non-neoplastic tissues,” Neoplasia, vol. 2, pp. 89-117, 2000.
[65] H. J. van Staveren, R. L. van Veen, O. C. Speelman, M. J. Witjes, W. M. Star, and J. L. Roodenburg, “Classification of clinical autofluorescence spectra of oral leukoplakia using an artificial neural network: a pilot study,” Oral Oncology, vol. 36, pp. 286-293, 2000.
[66] D. L. Heintzelman, U. Utzinger, H. Fuchs, A. Zuluaga, K. Gossage, A. M. Gillenwater, R. Jacob, B. Kemp, and R. R. Richards-Kortum, “Optimal excitation wavelengths for in vivo detection of oral neoplasia using fluorescence spectroscopy,” Photochemistry and Photobiology, vol. 72, pp. 103-113, 2000.
[67] S. K. Majumder, S. K. Mohanty, N. Ghosh, P. K. Gupta, D. K. Jain, and F. Khan, ”A pilot study on the use of autofluorescence spectroscopy for diagnosis of the cancer of human oral cavity,” Current Science, vol. 79, pp. 1089-1094, 2000.
[68] K. Onizawa, N. Okamura, H. Saginoya, H. Yusa, T. Yanagawa, and H. Yoshida, “Analysis of fluorescence in oral squamous cell carcinoma,” Oral Oncology, vol. 38, pp. 343-348, 2002.
[69] M. G. Muller, T. A. Valdez, I. Georgakoudi, V. Backman, C. Fuentes, S. Kabani, N. Laver, Z. Wang, C. W. Boone, R. R. Dasari, S. M. Shapshay, and M. S. Feld, “Spectroscopic detection and evaluation of morphologic and biochemical changes in early human oral carcinoma,” Cancer, vol. 97, pp. 1681-1692, 2003.
[70] T. Tsai, H. M. Chen, C. Y. Wang, J. C. Tsai, C. T. Chen, and C. P. Chiang, ”In vivo autofluorescence spectroscopy of oral premalignant and malignant lesions: distortion of fluorescence intensity by submucous fibrosis,” Lasers in Surgery and Medicine, vol. 33, pp. 40-47, 2003.
[71] D. C. G. d. Veld, M. Skurichina, M. J. H. Witjes, R. P. W. Duin, D. J. C. M. Sterenborg, W. M. Star, and J. L. Roodenburg, “Autofluorescence characteristics of healthy oral mucosa at different anatomical sites,” Lasers in Surgery and Medicine, vol. 32, pp. 367-376, 2003.
[72] D. C. de Veld, M. Skurichina, M. J. Witjes, R. P. Duin, H. J. Sterenborg, and J. L. Roodenburg, “Clinical study for classification of benign, dysplastic, and malignant oral lesions using autofluorescence spectroscopy,” Journal of Biomedical Optics, vol. 9, pp. 940-950, 2004.
[73] D. C. G. de Veld, M. Skurichina, M. J. H. Witjes, R. P. W. Duin, H. J. C. M. Sterenborg, and J. L. N. Roodenburg, “Autofluorescence and diffuse reflectance spectroscopy for oral oncology,” Lasers in Surgery and Medicine, vol. 36, pp. 356-364, 2005.
[74] J. L. Jayanthi, R. J. Mallia, S. T. Shiny, K. V. Baiju, A. Mathews, R. Kumar, P. Sebastian, J. Madhavan, G. N. Aparna, and N. Subhash, “Discriminant analysis of autofluorescence spectra for classification of oral lesions in vivo,” Lasers in Surgery and Medicine, vol. 41, pp. 345-352, 2009.
[75] D. Roblyer, C. Kurachi, A. M. Gillenwater, and R. Richards-Kortum, “In vivo fluorescence hyperspectral imaging of oral neoplasia,” Proceeding of SPIE, vol. 7169, pp. 71690J, 2009.
[76] D. Roblyer, C. Kurachi, V. Stepanek, M. D. Williams, A. K. El-Naggar, J. J. Lee, A. M. Gillenwater, and R. Richards-Kortum, “Objective detection and delineation of oral neoplasia using autofluorescence imaging,” Cancer Prevention Research, vol. 2, pp. 423-431, 2009.
[77] P. Chaturvedi, S. K. Majumder, H. Krishna, S. Muttagi and P. K. Gupta, “Fluorescence spectroscopy for noninvasive early diagnosis of oral mucosal malignant and potentially malignant lesions,” Journal of Cancer Research and Therapeutics, vol. 6, pp. 497-502, 2010.
[78] N. Bedard, R. A. Schwarz, A. Hu, V. Bhattar, J. Howe, M. D. Williams, A. M. Gillenwater, R. R. Kortum, and T. S. Tkaczyk, “Multimodal snapshot spectral imaging for oral cancer diagnostics- a pilot study,” Biomedical Optics Express, vol. 4, pp. 938-949, 2013.
[79] J. R. Duann, C. I. Jan, M. Ou-Yang, C. Y. Lin, J. F. Mo, Y. J. Lin, M. H. Tsai, and J. C. Chiou, “Separating spectral mixtures in hyperspectral image data using independent component analysis: validation with oral cancer tissue sections,” Journal of Biomedical Optics, vol. 18, pp. 126005, 2013.
[80] H. Tsurui, J. M. Lerner, K. Takahashi, S. Hirose, K. Mitsui, K. Okumura, and T. Shirai, “Hyperspectral imaging of pathology samples,” Proceeding of SPIE, vol. 3605, pp. 273-281, 1999.
[81] R. Schultz, T. Nielsen, J. Zavaleta, R. Ruch, R. Wyatt, and H. Garner, “Hyperspectral imaging: a novel approach for microscopic analysis,” Cytometry, vol. 43, pp. 239-247, 2001.
[82] B. S. Sorg, B. J. Moeller, O. Donovan, Y. Cao, and M. W. Dewhirst, “Hyperspectral imaging of hemoglobin saturation in tumor microvasculature and tumor hypoxia development,” Journal of Biomedical Optics, vol. 10, pp. 44004, 2005.
[83] M. E. Martin, M. B. Wabuyele, K. Chen, P. Kasili, M. Panjehpour,M. Phan, B. Overholt, G. Cunningham, D. Wilson, R. C. DeNovo, and T. Vo-Dinh, “Development of an hyperspectral imaging (HSI) system with applications for cancer detection,” Annals of Biomedical Engineering, vol. 34, pp. 1061-1068, 2006.
[84] D. T. Dicker, J. Lerner, P. V. Belle, S. F. Barth, D. Guerry, M. Herlyn, D. E. Elder, and W. S. El-Deiry, “Differentiation of normal skin and melanoma using high resolution hyperspectral imaging,” Cancer Biology and Therapy, vol. 5, 1033-1038, 2006.
[85] K. Masood, N. Rajpoot, K. Rajpoot, and H. Qureshi, “Hyperspectral colon tissue classification using morphological analysis,” IEEE 2th International Conference on Emerging Technologies, pp. 735-741, 2006.
[86] A. M. Siddiqi, H. Li, F. Faruque,W. Williams, K. Lai, M. Hughson, S. Bigler, J. Beach, and W. Johnson, “Use of hyperspectral imaging to distinguish normal, precancerous, and cancerous cells,” Cancer Cytopathology, vol. 114, 13-21, 2008.
[87] K. Masood and N. M. Rajpoot, “Classification of colon biopsy samples by spatial analysis of a single spectral band from its hyperspectral cube,” in Proceedings Medical Image Understanding and Analysis (MIUA), pp. 42-48, 2007.
[88] K. Masood and N. Rajpoot, “Texture based classification of hyperspectral colon biopsy samples using CLBP,” in IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 1011-1014, 2009.
[89] H. Akbari, K. Uto, Y. Kosugi, K. Kojima, and N. Tanaka, “Cancer detection using infrared hyperspectral imaging,” Cancer Science, vol. 102, pp. 852-857, 2011.
[90] D. Sebiskveradze, V. Vrabie, C. Gobinet, A. Durlach, P. Bernard, E. Ly, M. Manfait, P. Jeannesson, O. Piot, “Automation of an algorithm based on fuzzy clustering for analyzing tumoral heterogeneity in human skin carcinoma tissue sections,” Lab Invest, vol. 91, pp. 799-811, 2011.
[91] H. Akbari, L. V. Halig, D. M. Schuster, A. Osunkoya, V. Master, P. T. Nieh, G. Z. Chen, and B. Fei “Hyperspectral imaging and quantitative analysis for prostate cancer detection,” Journal of Biomedical Optics, vol. 17, pp. 076005, 2012.
[92] B. Fei, H. Akbari , L. V. Halig, “Hyperspectral imaging and spectral-spatial classification for cancer detection,” in Proceedings of IEEE Conference on Biomedical Engineering and Informatics (BMEI), pp. 62-64, 2012.
[93] H. Akbari, L. V. Halig, H. Zhang, D. Wang , Z. G. Chen, and B. Fei, “Detection of cancer metastasis using a novel macroscopic hyperspectral method,” Proceeding of SPIE , vol. 8317, pp. 831711, 2012.
[94] S. Kiyotoki, J. Nishikawa, T. Okamoto, K. Hamabe, M. Saito, A. Goto, Y. Fujita, Y. Hamamoto, Y. Takeuchi, S. Satori, and I. Sakaida. “New method for detection of gastric cancer by hyperspectral imaging: a pilot study,” Journal of Biomedical Optics, vol. 18, pp. 026010, 2013.
[95] G. Lu and B. Fei, “Medical hyperspectral imaging: a review,” Journal of Biomedical Optics, vol. 19, pp. 010901, 2014.
[96] Y. F. Hsieh, M. Ou-Yang, and C. C. Lee, “Finite conjugate embedded relay lens hyperspectral imaging system (ERL-HIS),” Applied Optics, vol. 50, pp. 6198-6205, 2011.
[97] W. J. Smith, Modern Optical Engineering: McGraw-Hill, 2000.
[98] D. Malacara, Geometrical and Instrumental Optics: Academic, 1988.
[99] R. E. Fisher and B. T. Galeb, Performance evaluation and optical testing: SPIE, 2000.
[100] C. S. Yang, Development of noninvasive apparatus for oral cancer diagnosis: National Chiao Tung University, Master thesis, 2013.
[101] A. Jemal, R. Siegel, J. Xu, and E. Ward, “Cancer statistics, 2010,” CA: A Cancer Journal for Clinicians, vol. 60, pp. 277-300, 2010.
[102] Y. F. Hsieh, M. Ou-Yang, J. R. Duann, J. C. Chou, N. W. Chang, C. I. Jan, M. H. Tsai, S. D. Wu, Y. J. Lin, and C. C. Lee, “Development of a Novel Embedded Relay Lens Microscopic Hyperspectral Imaging (ERL-MHSI) System for Cancer Diagnosis: Use the Mice with Oral Cancer to be the Example,” International Journal of Spectroscopy, vol. 2012, pp. 1-13, 2012.
[103] N. W. Chang, M. H. Tsai, C. Lin, H. T. Hsu, P. Y. Chu, C. M. Yeh, C. F. Chiu, and K. T. Yeh, “Fenofibrate exhibits a high potential to suppress the formation of squamous cell carcinoma in an oral-specific 4-nitroquinoline 1-oxide/arecoline mouse model,” Biochimica et Biophysica Acta, vol. 1812, pp. 558-564, 2011.
[104] F. Kenneth, Fractal Geometry: Wiley, 2003.
[105] C. S. Chen, Detection of oral cancer using embedded relay lens microscopic hyperspectral imaging system (ERL-MHIS): National Chiao Tung University, Master thesis, 2012.
[106] S. Warnakulasuriya, J. Reibel, J. Bouquot, and E. Dabelsteen, “Oral epithelial dysplasia classification systems: predictive value, utility, weaknesses and scope for improvement,” Journal of Oral Pathology & Medicine, vol. 37, pp. 127-133, 2008.
[107] D. T. Dicker, J. M. Lerner, and W. S. El-Deiry, “Hyperspectral image analysis of live cells in various cell cycle stages,” Cell Cycle, vol. 6, pp. 2563-2570, 2007.
[108] C. E. Metz, “Basic principles of ROC analysis,” Seminars in Nuclear Medicine, vol. 8, pp. 283-298, 1978.
[109] I. Pavlova, M. Williams, A. EI-Naggar, R. Richards-Kortum R, and A. Gillenwater, “Understanding the biological basis of autofluorescence imaging for oral cancer detection: high-resolution fluorescence microscopy in viable tissue,” Clinical Cancer Research, vol. 14, pp. 2396-2404, 2008.
[110] S. T. Lee, Cancer Detection of Mucosa Tissues by Epithelium and Lamina Propria Classification Based on Hyperspectral Imaging System (HIS): National Chiao Tung University, Master thesis, 2013.
[111] K. Pearson, On Lines and Planes of Closest Fit to Systems of Points in Space: University College, 1901.
[112] Q. Gu, Z. Li, and J. Han, “Generalized Fisher Score for Feature Selection,” Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, pp. 14-17, 2011.
[113] J. Han, M. Kamber, and J. Pei, Data Mining, Concepts and Techniques: Elsevier Science, 2006.
[114] D. G. Altman and J. M. Bland, “Statistics Notes: Diagnostic tests 1: sensitivity and specificity,” BMJ, vol. 308, pp. 1552, 1994.
[115] R. Kumar and A. Indrayan, “Receiver operating characteristic (ROC) curve for medical researchers,” Indian Pediatrics, vol. 48, pp. 277-287, 2011.
指導教授 歐陽盟、李正中(Mang Ou-Yang Cheng-Chung Lee) 審核日期 2014-11-10
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明