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題名 單一微生物粒子電性量測晶片與細菌影像辨識系統之開發
Development of electrical measurement-based single bioparticle tandem analyzer and bacteria image processing system.作者 朱自在 貢獻者 李尚凡
朱自在關鍵詞 微米電極
細菌辨識
單生物粒子電性量測日期 2017 上傳時間 13-九月-2017 14:50:35 (UTC+8) 摘要 此篇論文的第一部分為單一微粒子電特性測量微型晶片之開發，希望能達到微量微米尺度樣品之免標定、實時、原地、單個體、非專一性之量測與辨認。而欲達成此晶片所需之五大概念為： 一、利用微米製程製作，可用於微小單分子測量。二、微晶片體積小，利於實地測量。三、不同物體電特性之差異可用於單一生物個體之辨認，補足了純統計測量不足之處。四、電特性之測量不須標定，任何尺寸符合之生物分子皆可測量。五、電特性有著可實時測量之性質。電特性測量晶片之製作概念為將待測樣品流過夾於微米電極之間的微米流道，而電極向外延伸，外接電特性測量工具，使樣品流過電極之時可以進行電特性之測量。晶片的製作上需要利用黃光微米製程於石英玻璃基板上製作多個微米電極陣列與置於電極間之單一微米流道。目前已完成微米分子電特性測量晶片之製程，並且可以利用螢光顯微鏡觀測到測試用螢光珠穿過微米電極之影像，且已觀測到導電溶液流過電極時電極導通之現象，顯示出微米尺寸下單一粒子電特性測量之可能性。 此篇論文的第二部分為單一微生物辨認影像處理系統之開發，希望能減少單一細菌個體之影像特性取得所需要的人力與時間，並且使其結果更加客觀。單一細菌辨認影像處理最重要的步驟為不同細菌之間的切割分離，然而對於擁擠且低解析度的細菌影像，此步驟的困難度又更加提升。於此篇論文中，我們引入了主曲率邊緣強化法，此方法可以有效的增強細菌邊緣之對比，減少細菌的切割與分離步驟之困難度。目前已完成一般且擁擠之情況下之半自動細菌影像辨認系統，擁有約九成以上的辨認成功率。 參考文獻 1.U.S. Environmental Protection Agency (USEPA). 2002. Method 1603: Escherichia coli (E. coli) in water by membrane filtration using Modifed membrane ¡V Thermotolerant Escherichia coli (Modified mTEC). EPA-821-R-02-023. Office of Water (4303T), Washington, D.C.2.Chris A. Rowe. et al, 1999. Array Biosensor for Simultaneous Identification of Bacterial, Viral, and Protein Analytes. Analytical Chenistry. 71. 17. 3846-3852. 3.Guo, Zhiyong. et al, 2016. Faraday cage-type electrochemiluminescence immunosensor for ultrasensitive detection of Vibrio vulnificus based on multi-functionalized graphene oxide.Analytical And Bioanalytical Chemistry. 408. 25. 7203-7211. 4.Leonardo Lesser-Rojas. et al, 2014. Tandem array of nanoelectronic readers embedded coplanar to a fluidic nanochannel for correlated single biopolymer analysis. Biomicrofluidics. 8. 016501.5. O. Sliusarenko. et al, 2011. Highthroughput, subpixel precision analysis of bacterial morphogenesis and intracellular spatio-temporal dynamics. Mol. Microbiol. 80. 612–627.6. J. W. Young. et al, 2012. Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat. Protocols. 1. 80–887.Sajith Kecheril Sadanandan. et al, 2016. Segmentation and Track-analysis in Time-lapse Imaging of Bacteria. IEEE Journal of Selected Topics in Signal Processing . 10, 174-184.8.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. Chapter 1.9.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. Chapter 2.10.Jaeger, Richard C, 2002. Introduction to Microelectronic Fabrication 2nd edition, Prentice Hall. Chapter 6.1.11.Mark, J. E., Allcock, H. R. West, R, 2005. Inorganic Polymers 2nd Edition, Oxford University Press. Chapter 4.12.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. 18.13.Rafael C. Gonzalez Richard, E. Woods, 2008. Digital Image Processing 3rd Edition, Prentice Hall. Chapter 4.14.DENG, G. et al, 1993. An adaptive Gaussian filter for noise reduction and edge detection. In: Nuclear Science Symposium and Medical Imaging Conference. IEEE Conference Record. IEEE. 1615-1619.15.HUANG, T. et al, 1979. A fast two-dimensional median filtering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing. 27.1, 13-18.16.TANAKA, Hiromi T. et al, 1998. Curvature-based face surface recognition using spherical correlation. principal directions for curved object recognition. In: Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on. IEEE. 372-377.17.S. Q. Wang, 2005. Optimized condition for etching fused-silica phase gratings with inductively coupled plasma technology, Applied Optics. 44, 4429.18.Moazzez, Behrang. et al, 2013. Improved Adhesion of Gold Thin Films Evaporated on Polymer Resin: Applications for Sensing Surfaces and MEMS, Sensors. 13, 7021. 描述 碩士
國立政治大學
應用物理研究所
104755006資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104755006 資料類型 thesis dc.contributor.advisor 李尚凡 zh_TW dc.contributor.author (作者) 朱自在 zh_TW dc.creator (作者) 朱自在 zh_TW dc.date (日期) 2017 en_US dc.date.accessioned 13-九月-2017 14:50:35 (UTC+8) - dc.date.available 13-九月-2017 14:50:35 (UTC+8) - dc.date.issued (上傳時間) 13-九月-2017 14:50:35 (UTC+8) - dc.identifier (其他 識別碼) G0104755006 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112682 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 應用物理研究所 zh_TW dc.description (描述) 104755006 zh_TW dc.description.abstract (摘要) 此篇論文的第一部分為單一微粒子電特性測量微型晶片之開發，希望能達到微量微米尺度樣品之免標定、實時、原地、單個體、非專一性之量測與辨認。而欲達成此晶片所需之五大概念為： 一、利用微米製程製作，可用於微小單分子測量。二、微晶片體積小，利於實地測量。三、不同物體電特性之差異可用於單一生物個體之辨認，補足了純統計測量不足之處。四、電特性之測量不須標定，任何尺寸符合之生物分子皆可測量。五、電特性有著可實時測量之性質。電特性測量晶片之製作概念為將待測樣品流過夾於微米電極之間的微米流道，而電極向外延伸，外接電特性測量工具，使樣品流過電極之時可以進行電特性之測量。晶片的製作上需要利用黃光微米製程於石英玻璃基板上製作多個微米電極陣列與置於電極間之單一微米流道。目前已完成微米分子電特性測量晶片之製程，並且可以利用螢光顯微鏡觀測到測試用螢光珠穿過微米電極之影像，且已觀測到導電溶液流過電極時電極導通之現象，顯示出微米尺寸下單一粒子電特性測量之可能性。 此篇論文的第二部分為單一微生物辨認影像處理系統之開發，希望能減少單一細菌個體之影像特性取得所需要的人力與時間，並且使其結果更加客觀。單一細菌辨認影像處理最重要的步驟為不同細菌之間的切割分離，然而對於擁擠且低解析度的細菌影像，此步驟的困難度又更加提升。於此篇論文中，我們引入了主曲率邊緣強化法，此方法可以有效的增強細菌邊緣之對比，減少細菌的切割與分離步驟之困難度。目前已完成一般且擁擠之情況下之半自動細菌影像辨認系統，擁有約九成以上的辨認成功率。 zh_TW dc.description.tableofcontents Chapter 1 Introduction 8Chapter 2 Device Fabrication 11Section 2.1 Fabrication Techniques 11Column 2.1.1 Photolithography 11Column 2.1.2 Anisotropic Dry Etching 12Column 2.1.3 Thermal Evaporation Metal Deposition 13Column 2.1.4 Polydimethylsiloxane(PDMS) Bonding 14Section 2.2 Device Design 15Section 2.3 Fabrication Steps 18Chapter 3 Bacteria Image Processing System 20Section 3.1 Overview 20Section 3.2 Image Processing Techniques 21Column 3.2.1 Fast Fourier Transform Filter 21Column 3.2.2 Gaussian Blur 23Column 3.2.3 Median Filter 24Column 3.2.4 Principal Curvatures Edge Enhancement 25Column 3.2.5 Binarization 26Section 3.3 Program Design 27Chapter 4 Result and Discussion 31Section 4.1 Instrument Calibration and Initial Tests 31Section 4.2 Electrical Properties Measurement Device 34Column 4.2.1 Device Fabrication 34Column 4.2.2 Device Tests 39Section 4.3 Bacteria Image Processing System 44Section 4.4 Discussion 53Chapter 5 Conclusion and Future Works 54References 55 zh_TW dc.format.extent 3752305 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104755006 en_US dc.subject (關鍵詞) 微米電極 zh_TW dc.subject (關鍵詞) 細菌辨識 zh_TW dc.subject (關鍵詞) 單生物粒子電性量測 zh_TW dc.title (題名) 單一微生物粒子電性量測晶片與細菌影像辨識系統之開發 zh_TW dc.title (題名) Development of electrical measurement-based single bioparticle tandem analyzer and bacteria image processing system. en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 1.U.S. Environmental Protection Agency (USEPA). 2002. Method 1603: Escherichia coli (E. coli) in water by membrane filtration using Modifed membrane ¡V Thermotolerant Escherichia coli (Modified mTEC). EPA-821-R-02-023. Office of Water (4303T), Washington, D.C.2.Chris A. Rowe. et al, 1999. Array Biosensor for Simultaneous Identification of Bacterial, Viral, and Protein Analytes. Analytical Chenistry. 71. 17. 3846-3852. 3.Guo, Zhiyong. et al, 2016. Faraday cage-type electrochemiluminescence immunosensor for ultrasensitive detection of Vibrio vulnificus based on multi-functionalized graphene oxide.Analytical And Bioanalytical Chemistry. 408. 25. 7203-7211. 4.Leonardo Lesser-Rojas. et al, 2014. Tandem array of nanoelectronic readers embedded coplanar to a fluidic nanochannel for correlated single biopolymer analysis. Biomicrofluidics. 8. 016501.5. O. Sliusarenko. et al, 2011. Highthroughput, subpixel precision analysis of bacterial morphogenesis and intracellular spatio-temporal dynamics. Mol. Microbiol. 80. 612–627.6. J. W. Young. et al, 2012. Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat. Protocols. 1. 80–887.Sajith Kecheril Sadanandan. et al, 2016. Segmentation and Track-analysis in Time-lapse Imaging of Bacteria. IEEE Journal of Selected Topics in Signal Processing . 10, 174-184.8.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. Chapter 1.9.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. Chapter 2.10.Jaeger, Richard C, 2002. Introduction to Microelectronic Fabrication 2nd edition, Prentice Hall. Chapter 6.1.11.Mark, J. E., Allcock, H. R. West, R, 2005. Inorganic Polymers 2nd Edition, Oxford University Press. Chapter 4.12.MarcJ.Madou, 2002. Fundamentals of Microfabrication 2nd Edition, CRC Press. 18.13.Rafael C. Gonzalez Richard, E. Woods, 2008. Digital Image Processing 3rd Edition, Prentice Hall. Chapter 4.14.DENG, G. et al, 1993. An adaptive Gaussian filter for noise reduction and edge detection. In: Nuclear Science Symposium and Medical Imaging Conference. IEEE Conference Record. IEEE. 1615-1619.15.HUANG, T. et al, 1979. A fast two-dimensional median filtering algorithm. IEEE Transactions on Acoustics, Speech, and Signal Processing. 27.1, 13-18.16.TANAKA, Hiromi T. et al, 1998. Curvature-based face surface recognition using spherical correlation. principal directions for curved object recognition. In: Automatic Face and Gesture Recognition, 1998. Proceedings. Third IEEE International Conference on. IEEE. 372-377.17.S. Q. Wang, 2005. Optimized condition for etching fused-silica phase gratings with inductively coupled plasma technology, Applied Optics. 44, 4429.18.Moazzez, Behrang. et al, 2013. Improved Adhesion of Gold Thin Films Evaporated on Polymer Resin: Applications for Sensing Surfaces and MEMS, Sensors. 13, 7021. zh_TW
