請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65427完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 宋孔彬(Kung-Bin Sung) | |
| dc.contributor.author | Chong-Ian Mok | en |
| dc.contributor.author | 莫松恩 | zh_TW |
| dc.date.accessioned | 2021-06-16T23:42:14Z | - |
| dc.date.available | 2025-02-25 | |
| dc.date.copyright | 2020-02-25 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2020-02-19 | |
| dc.identifier.citation | 1. 死因統計結果分析-衛生署福利部統計署
2. SHENG-YANG TSUI, CHIAO-YI WANG, TSAN-HSUEH HUANG, 'Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations, Vol. 9, No. 4 | 1 Apr 2018 | BIOMEDICAL OPTICS EXPRESS 1531 3. Rebekah Drezek, Iouri Boiko, Michele Follen, et al., 'Understanding the contributions of NADH and collagen to cervical tissue fluorescence spectra: Modeling, measurements, and implications', Journal of Biomedical Optics 6(4), 385–396 (October 2001) 4. George D. Birkmayer and Jiren Zhang, 'NADH in Cancer Prevention and Therapy', Phytopharmaceuticals in Cancer Chemoprevention. 5. Pelzmann B, Hallström S, Schaffer P, Lang P, Nadlinger, K, Birkmayer GD, et al (2003) NADH supplementation decreases pinacidil‐primed IK (ATP) in ventricular cardiomyocytes by increasing intracellular ATP. Brit J Pharmacol 139(4):749-754. 6. C. InceJ. M. C. C. CoremansH. A. Bruining, 'In Vivo NADH Fluorescence', Oxygen Transport to Tissue XIV pp 277-296 7. S. V. Frolov, A. Yu. Potlov, D. A. Petrov, S. G. Proskurin, “Monte-Carlo simulation of OCT structural images of human skin using experimental B-scans and voxel based approach to optical properties distribution”, 2016, Fourth International Symposium on Optics and Biophotonics. 8. Sinan Zhao, “Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography”, 2016, California Institute of Technology Pasadena, California. 9. Lingyan Shi, Luyao Lu, George Harvey, Thomas HarveyL, et. al., label-Free Fluorescence Spectroscopy for Detecting Key Biomolecules in Brain Tissue from a Mouse Model of Alzheimer’s Disease, Scientific Reports volume 7, Article number: 2599 (2017) 10. D. R. Eyre, M. A. Paz, and P. M. Gallop, “Cross-linking in collagen and elastin,” Annu. Rev. Biochem. 53, 717–748 (1984). 11. Henyey, Louis G., and Jesse Leonard Greenstein. 'Diffuse radiation in the galaxy.' The Astrophysical Journal 93 (1941): 70 83.S. Prahl, Optical Absorption of Hemoglobin, Oregon Medical Laser Center, 1999. 12. A. J. Welch, Craig Gardner, Rebecca Richards‐Kortum, et al., 'Propagation of fluorescent light', Lasers Surg. Med. 21:166–178, 1997. 13. Emilie Pery; Walter C. P. M. Blondel; Cedric Thomas, et al., 'Monte Carlo modeling of multilayer phantoms with multiple fluorophores: simulation algorithm and experimental validation', J. of Biomedical Optics, 14(2), 024048 (2009). 14. Farrell TJ1, Patterson MS, Wilson B., 'A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo.', send to Med Phys. 1992 Jul-Aug;19(4):879-88. 15. Qu, Jianan, et al. 'Optical properties of normal and carcinomatous bronchial Applied optics 33.31 (1994): 7397 7405. 16. Nunez, Abel S A physical model of human skin and its application for search and rescue. No. AFIT/DEO/ENG/09 14. AIR FORCE INST OF TECH WRIGHT PATTERSON AFB OH SCHOOL OF ENGINEERING, 2009. 17. Tom Collier, Dizem Arifler, Anais Malpica, et al. 'Determination of Epithelial Tissue Scattering Coefficient Using Confocal Microscopy',IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, VOL. 9, NO. 2, MARCH/APRIL 2003 18. Tom Collier, Michele Follen, Anais Malpica, and Rebecca Richards-Kortum, 'Sources of scattering in cervical tissue: determination of the scattering coefficient by confocal microscopy', APPLIED OPTICS Vol. 44, No. 11, 10 April 2005 19. A. Bhandari, B. Hamre, Ø. Frette, K. Stamnes, and J. J. Stamnes, 'Modeling optical properties of human skin using Mie theory for particles with different size distributions and refractive indices', 18 July 2011 / Vol. 19, No. 15 / OPTICS EXPRESS 14549. 20. Tsan Hsueh Huang, “Quantifying In-Vivo Tissue Optical Parameters of Precancerous Cervical Lesions using a Portable Reflectance Spectroscopy System”, National Taiwan University 21. Min-Jie Chuang, 'Construction and Verification of a Portable Diffuse Reflectance Spectroscopy System for Clinical Studies 22. Yi-Hsien Hsiao, 'Using Fluorescence Spectroscopy to Distinguish Precancerous Mucosa', National Taiwan University. 23. Sheng-Yang Tsui, Chiao-Yi Wang, Tsan-Hsueh Huang, and Kung-Bin Sung, 'Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations', Biomed Opt Express. 2018 Apr 1; 9(4): 1531–1544. 24. T.Jayalakshmi, Dr.A.Santhakumaran, 'Statistical Normalization and Back Propagation for Classification', International Journal of Computer Theory and Engineering, Vol.3, No.1, February, 2011 1793-8201. 25. Azzalini, Adelchi; Capitanio, Antonella (2014). The skew-normal and related families. pp. 32–33. ISBN 978-1-107-02927-9. 26. Ting-Wen Yu, Gen-Hao Tien, Fang-Wei Hsu, Kung-Bin Sung, 'Extracting Fluorescence Efficiency with a GPU-Based Monte Carlo Model for Two-Layer Mucosal Tissue', Biomedical Optics Congress 2016 (Brain, Cancer, OTS, Translational), OSA 2016 27. Shih-Cheng Tu, Kung-Bin Sung, “Extracting fluorescence efficiency and emission spectra of cervical tissue”, Frontiers in Optics / Laser Science © OSA 2018 28. Md. Serajul Islam , Masato Honma , Takakazu Nakabayashi, et al., 'pH Dependence of the Fluorescence Lifetime of FAD in Solution and in Cells', Int. J. Mol. Sci. 2013, 14, 1952-1963. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65427 | - |
| dc.description.abstract | 本文中確立了兩段式曲線擬合(curve fitting)的流程，用於分析子宫頸處的漫反射光譜(diffuse reflection spectrum, DRS)以及螢光光譜(fluorescence spectrum)，計算子宫頸黏膜組織之光學參數及主要螢光物質的螢光產率(fluorescence efficiency)，可用於研究兩種光譜與子宫頸癌之關係。兩段式曲線擬合包含曲線擬合及基因演算法(genetic algorithm)兩部份，第一段曲線擬合用於擬合臨床漫反射光譜，擬合模型為蒙地卡羅法(Monte Carlo method)，求出組織兩層吸收(absorption)、散射(scattering)係數；蒙地卡羅法為利用亂數進行模擬的演算法，用於模擬光子在組織中的運動；第二段使用基因演算法之最佳化流程解出組織中主要螢光物質的螢光產率及放光機率，擬合放光機率所使用的擬合模型為偏態分佈(skewed distribution)。目前普遍提取子宫頸處螢光光譜中的光學資訊所使用的組織模型大部份為單層結構，本文中使用半無窮深的兩層結構來模擬子宫頸組織，藉由分離兩層組織光譜的方式來描述處於不同層中激發不同螢光物質所放出之螢光。本文中提出了利用兩層組織模擬子宫頸組織之擬合方法，能夠從漫反射光譜及螢光光譜提取出組織中的吸收係數、散射係數、上層厚度，以及三種主要螢光物質螢光產率。另外，若曲線擬合中使用蒙地卡羅法作為擬合模型，需時較久；因此本文中利用類神經網路(artificial neuron network, ANN)取代蒙地卡羅法進行模擬，能夠提高估計組織光學參數的效率。 | zh_TW |
| dc.description.abstract | In this study, two-step curve fitting process is established for analysis of diffuse reflection spectrum and fluorescence spectrum of cervix tissue in clinical, which provides information for diagnosis of cervical cancer. Optical parameters of cervix tissue and fluorescence efficiency of three main fluorescent materials in tissue can be calculated by this process. Two-step curve fitting includes two parts: curve fitting and genetic algorithm (GA). First, absorption and scattering coefficient can be calculated by curve fitting. Monte Carlo method is a fitting model of curve fitting, which is used for stimulation of photon movement in tissue. Second, fluorescence efficiency and emission probability of main fluorescent materials can be computed by genetic algorithm. Fitting model of genetic algorithm is skewed distribution, which is for simulation of emission probability. One-layer tissue model is applied as a common model for extraction of optical information from tissue, mainly on cervix tissue. This study suggests a fitting process using two-layer tissue model for optical simulation, which can extract absorption and scattering coefficient of upper and lower layer, thickness of upper layer, fluorescence efficiency and emission probability of three main fluorescent materials. On the other hand, Monte Carlo method is a fitting model of curve fitting process, which is time-consuming. Instead of Monte Carlo method, artificial neuron network can be applied for enhancing the efficiency of predicting optical parameters. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T23:42:14Z (GMT). No. of bitstreams: 1 ntu-108-R06945043-1.pdf: 2410715 bytes, checksum: 7f2bcdb4da20c05890ec53d88e1b76b2 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 致謝 i
中文摘要 ii Abstract iii 目錄 iv 圖目錄 vi 表目錄 viii 第一章、緒論 1 1.1 前言 1 1.2 背景 1 1.3 研究動機 2 第二章、理論基礎 3 2.1 概述 3 2.2 漫反射原理 4 2.3 螢光原理 5 2.4 蒙地卡羅法 7 2.4.1 概述 7 2.4.2 算術模型 7 2.4.3 螢光蒙地卡羅法 10 2.4.4 雙層組織模型 12 2.5 類神經網路 14 2.6 曲線擬合 15 2.7 基因演算法 16 第三章、研究方法 18 3.1 概論 18 3.2 臨床實驗 18 3.2.1 臨床光學系統 18 3.2.2 臨床漫反射光譜校正 20 3.2.3 臨床螢光光譜校正 22 3.3 建立螢光用類神經網路 24 3.3.1 類神經網路訓練資料 24 3.3.2 建立類神經網路 24 3.3.3 輸入輸出之數據處理 26 3.4 曲線擬合 28 3.4.1 篩選初始值流程 29 3.4.2 兩段式曲線擬合 30 3.5 產生測試光譜 37 3.5.1 漫反射測試光譜 37 3.5.2 螢光測試光譜 40 第四章 研究結果 43 4.1 螢光用類神經網路 43 4.1.1 類神經網路訓練 43 4.1.2 類神經網路訓練(利用原始模擬光強數據) 47 4.1.3 螢光蒙地卡羅法之變異係數 47 4.2 曲線擬合 49 4.2.1 膠原蛋白濃度對光譜之影響 49 4.2.2 測試光譜擬合 49 4.3 對臨床光譜進行擬合 55 4.4 臨床螢光光譜分析 58 第五章 結論與未來展望 60 5.1 結論 60 5.2 未來展望與討論 61 參考文獻 62 | |
| dc.language.iso | zh-TW | |
| dc.subject | 漫反射光譜 | zh_TW |
| dc.subject | 基因演算法 | zh_TW |
| dc.subject | 類神經網路 | zh_TW |
| dc.subject | 蒙地卡羅法 | zh_TW |
| dc.subject | 螢光光譜 | zh_TW |
| dc.subject | Diffuse reflection spectrum | en |
| dc.subject | Fluorescence spectrum | en |
| dc.subject | Monte Carlo | en |
| dc.subject | Artificial neuron network | en |
| dc.subject | Genetic algorithm | en |
| dc.title | 兩段式曲線擬合結合雙層組織模型定量子宫頸組織的內在螢光特徵 | zh_TW |
| dc.title | Two-Step Curve Fitting Combined with Two-Layer Tissue Model for Quantitative of Intrinsic Fluorescence of Cervical Tissue | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 108-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳啟豪,江惠華 | |
| dc.subject.keyword | 漫反射光譜,螢光光譜,蒙地卡羅法,類神經網路,基因演算法, | zh_TW |
| dc.subject.keyword | Diffuse reflection spectrum,Fluorescence spectrum,Monte Carlo,Artificial neuron network,Genetic algorithm, | en |
| dc.relation.page | 62 | |
| dc.identifier.doi | 10.6342/NTU201904186 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2020-02-19 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| 顯示於系所單位： | 生醫電子與資訊學研究所 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 2.35 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。