請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79036
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 | Ting-Xuan Lin | en |
dc.contributor.author | 林廷軒 | zh_TW |
dc.date.accessioned | 2021-07-11T15:38:33Z | - |
dc.date.available | 2023-08-21 | |
dc.date.copyright | 2018-08-21 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-14 | |
dc.identifier.citation | 1. Crosson, B., et al., Functional imaging and related techniques: An introduction for rehabilitation researchers. Journal of rehabilitation research and development, 2010. 47(2): p. vii.
2. Irani, F., et al., Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders. The Clinical Neuropsychologist, 2007. 21(1): p. 9-37. 3. Durduran, T., et al., Diffuse optics for tissue monitoring and tomography. Reports on Progress in Physics, 2010. 73(7): p. 076701. 4. Lloyd-Fox, S., A. Blasi, and C. Elwell, Illuminating the developing brain: the past, present and future of functional near infrared spectroscopy. Neuroscience & Biobehavioral Reviews, 2010. 34(3): p. 269-284. 5. Gibson, A., et al., Three-dimensional whole-head optical tomography of passive motor evoked responses in the neonate. Neuroimage, 2006. 30(2): p. 521-528. 6. Auger, H., et al., Quantification of extra-cerebral and cerebral hemoglobin concentrations during physical exercise using time-domain near infrared spectroscopy. Biomedical optics express, 2016. 7(10): p. 3826-3842. 7. Quaresima, V., et al., Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study. Journal of biomedical optics, 2005. 10(1): p. 011012. 8. Giacalone, G., et al., Cerebral time domain-NIRS: reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects. Biomedical optics express, 2017. 8(11): p. 4987-5000. 9. Gagnon, L., et al., Double-layer estimation of intra-and extracerebral hemoglobin concentration with a time-resolved system. Journal of biomedical optics, 2008. 13(5): p. 054019. 10. Choi, J.H., et al., Noninvasive determination of the optical properties of adult brain: near-infrared spectroscopy approach. Journal of biomedical optics, 2004. 9(1): p. 221-230. 11. Hallacoglu, B., et al., Absolute measurement of cerebral optical coefficients, hemoglobin concentration and oxygen saturation in old and young adults with near-infrared spectroscopy. Journal of biomedical optics, 2012. 17(8): p. 081406. 12. Moreau, F., et al., Near-infrared measurements of brain oxygenation in stroke. Neurophotonics, 2016. 3(3): p. 031403. 13. Gatto, R.G., et al., Age effects on brain oxygenation during hypercapnia. Journal of biomedical optics, 2007. 12(6): p. 062113. 14. Dehghani, H., et al., Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography. Applied optics, 2009. 48(10): p. D137-D143. 15. Rajaram, A., et al., Simultaneous monitoring of cerebral perfusion and cytochrome c oxidase by combining broadband near-infrared spectroscopy and diffuse correlation spectroscopy. Biomedical Optics Express, 2018. 9(6): p. 2588-2603. 16. Yeganeh, H.Z., et al., Broadband continuous-wave technique to measure baseline values and changes in the tissue chromophore concentrations. Biomedical optics express, 2012. 3(11): p. 2761-2770. 17. Custo, A., et al., Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging. Applied optics, 2006. 45(19): p. 4747-4755. 18. Firbank, M., et al., Measurement of the optical properties of the skull in the wavelength range 650-950 nm. Physics in Medicine & Biology, 1993. 38(4): p. 503. 19. Simpson, C.R., et al., Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique. Physics in Medicine & Biology, 1998. 43(9): p. 2465. 20. Van der Zee, P., M. Essenpreis, and D.T. Delpy. Optical properties of brain tissue. in Photon Migration and Imaging in Random Media and Tissues. 1993. International Society for Optics and Photonics. 21. Zhan, Y., et al., Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model. Frontiers in neuroenergetics, 2012. 4: p. 6. 22. Liu, Y., et al., Monte Carlo and phantom study in the brain edema models. Journal of Innovative Optical Health Sciences, 2017. 10(03): p. 1650050. 23. Chuang, C.-C., et al., Patient-oriented simulation based on Monte Carlo algorithm by using MRI data. Biomedical engineering online, 2012. 11(1): p. 21. 24. Husain, K. Functional neuroanatomy of brain. 2014; Available from: https://www.slideshare.net/karrarhusain/functional-neuroanatomy-of-brain. 25. Ottenbacher, K.J. and S. Jannell, The results of clinical trials in stroke rehabilitation research. Archives of neurology, 1993. 50(1): p. 37-44. 26. Zhang, Y., J. Sun, and P. Rolfe, RLS adaptive filtering for physiological interference reduction in NIRS brain activity measurement: a Monte Carlo study. Physiological measurement, 2012. 33(6): p. 925. 27. Farrell, T.J., M.S. Patterson, and B. Wilson, A diffusion theory model of spatially resolved, steady‐state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo. Medical physics, 1992. 19(4): p. 879-888. 28. Wang, L., S.L. Jacques, and L. Zheng, MCML—Monte Carlo modeling of light transport in multi-layered tissues. Computer methods and programs in biomedicine, 1995. 47(2): p. 131-146. 29. Henyey, L.G. and J.L. Greenstein, Diffuse radiation in the galaxy. The Astrophysical Journal, 1941. 93: p. 70-83. 30. Prahl, S.A. A Monte Carlo model of light propagation in tissue. in Dosimetry of laser radiation in medicine and biology. 1989. International Society for Optics and Photonics. 31. Jacques, S.L. and D.J. McAuliffe, The melanosome: threshold temperature for explosive vaporization and internal absorption coefficient during pulsed laser irradiation. Photochemistry and photobiology, 1991. 53(6): p. 769-775. 32. Qu, J., et al., Optical properties of normal and carcinomatous bronchial tissue. Applied optics, 1994. 33(31): p. 7397-7405. 33. Jacques, S.L., Optical properties of biological tissues: a review. Physics in Medicine & Biology, 2013. 58(11): p. R37. 34. Nunez, A.S., A physical model of human skin and its application for search and rescue. 2009: Air Force Institute of Technology. 35. Buiteveld, H., J. Hakvoort, and M. Donze. Optical properties of pure water. in Ocean Optics XII. 1994. International Society for Optics and Photonics. 36. Sethuraman, S., et al., Spectroscopic intravascular photoacoustic imaging to differentiate atherosclerotic plaques. Optics express, 2008. 16(5): p. 3362-3367. 37. Bashkatov, A.N., E.A. Genina, and V.V. Tuchin, Optical properties of skin, subcutaneous, and muscle tissues: a review. Journal of Innovative Optical Health Sciences, 2011. 4(01): p. 9-38. 38. Nunez, A.S., A physical model of human skin and its application for search and rescue. 2009, AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING. 39. Okui, N. and E. Okada, Wavelength dependence of crosstalk in dual-wavelength measurement of oxy-and deoxy-hemoglobin. Journal of biomedical optics, 2005. 10(1): p. 011015. 40. Tsui, S.-Y., et al., Modelling spatially-resolved diffuse reflectance spectra of a multi-layered skin model by artificial neural networks trained with Monte Carlo simulations. Biomedical optics express, 2018. 9(4): p. 1531-1544. 41. Heiskala, J., et al., Modeling anisotropic light propagation in a realistic model of the human head. Applied optics, 2005. 44(11): p. 2049-2057. 42. Hennessy, R., et al., Effect of probe geometry and optical properties on the sampling depth for diffuse reflectance spectroscopy. Journal of biomedical optics,2014. 19(10): p. 107002. 43. 黃贊學 , 利用移動式漫反射光譜系統定量子宮頸癌前病變之組織學參數. 2017. 44. Boas, D.A. and A.M. Dale, Simulation study of magnetic resonance imaging–guided cortically constrained diffuse optical tomography of human brain function. Applied optics, 2005. 44(10): p. 1957-1968. 45. Custo, A., et al., Anatomical atlas-guided diffuse optical tomography of brain activation. Neuroimage, 2010. 49(1): p. 561-567. 46. Taga, G., F. Homae, and H. Watanabe, Effects of source-detector distance of near infrared spectroscopy on the measurement of the cortical hemodynamic response in infants. Neuroimage, 2007. 38(3): p. 452-460. 47. 王巧懿 , 修正式蒙地卡羅逆向擬合模型於活體漫反射光譜研究. 2016. 49. Meglinski, I.V. and S.J. Matcher, Quantitative assessment of skin layers absorption and skin reflectance spectra simulation in the visible and near-infrared spectral regions. Physiological measurement, 2002. 23(4): p. 741. 50. 賴鈺銘 , 功能性近紅外線光譜技術中探頭擺放決策的模擬研究 . 2016. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79036 | - |
dc.description.abstract | 近紅外光譜技術(NIRS, Near-infrared spectroscopy)已發展將近二十年,此技術通常應用在大腦組織中。由於大腦中有非常多血管,當受到刺激時,腦中的血紅素濃度、血氧飽和濃度會產生變化,此時就可以用近紅外光譜技術探討大腦中活化區域的變化,而這些變化的區域可以擴散光學斷層影像(Diffuse optical tomography,DOT)技術重建出三維空間的吸收分布區域。人體頭部基本上可分四層或五層組織,各層又有各自的光學參數,如吸收係數、散射係數,若要重建出大腦的活化區域,就需要出各層的光學參數。
本研究設計了一套實驗流程定量出人體頭部組織中各層之光學參數,為了量測人體頭部,建構了近紅外光譜系統,結合4 種探頭涵蓋12 個不同的光源-偵測器間距。利用蒙地卡羅演算法模擬光子在不同散射及吸收特性組織內之行進情形,藉此得到蒙地卡羅順向模擬光譜。接著量測已知光學參數的液態及固態仿體得到實驗光譜,將實驗光譜與模擬光譜進行系統校正去除掉系統響應造成的光譜不均勻性。為了要模擬人體頭部多層結構的特性,會以多層固態仿體證明系統可量測多層組織模型的可行性。經由仿體驗證完系統後,最後量測人體頭部靠近前額葉的區域,根據4種探頭量測不同頭部中各層的目標,各別以逆向光譜擬合工具萃取出各層的組織光學參數。 根據實驗結果,液態仿體與單層固態仿體實驗中,實驗值與模擬值之間具有非常高的線性度(R2 值均在0.99 以上),且經過校正後的實驗測量光譜與模擬光譜間的誤差很小。在多層固態仿體實驗中,各模型校正後的光譜誤差為,雙層模型: 3.15 %、三層模型: 7.8 %、四層模型:12.34 %,此校正結果驗證系統可量測多層組織。 最後人體頭部實驗中,由擬合結果再和前人研究文獻提及於波長750、780、830 nm所示的吸收與減少散射係數結果相當接近,證明了在本論文中所使用的方法流程是可定量多層組織的人體頭部組織光學參數。 | zh_TW |
dc.description.abstract | Near-infrared spectroscopy (NIRS) has been in development for two decades, and this technique is commonly used in brain tissue. Since there are many blood vessels in the brain, when the stimulus is stimulated, the concentration of hemoglobin and the concentration of blood oxygen in the brain will change. At this time, the near-infrared spectroscopy technique can be used to explore the changes in the activation region in the brain. Diffuse optical tomography (DOT) technology can be used to reconstruct the absorption distribution region in three-dimensional. The human head can be divided into four or five layers. Each layer has its own optical parameters, such as absorption coefficient and scattering coefficient. To reconstruct the activation region of the brain, the optical parameters of each layer are required.
In this study, experimental procedures were designed to quantify the optical parameters of each layer in a four-layered human head model: the scalp, skull, cerebrospinal fluid, and cerebral cortex. A NIRS system combined four probes that covered 12 different source-to-detector separations (SDS) in the range of 0.215-32.4 mm for multiple depth resolved measurements. Calibration was performed by measuring spectra of phantoms of known optical parameters and comparing to corresponding simulated spectra using the Monte Carlo method. In order to simulate the characteristics of the multi-layer structure of the human head, the feasibility of the multi-layered tissue model can be measured by a multi-layer solid-like profiling system. After verifying the system through the phantom, the human head is measured near the area of the prefrontal lobe. The targets of each layer in the different heads are measured according to the four kinds of probes,Shallower layers were measured with smaller SDS and extracted optical properties were used as initial estimates for later quantification of all four layers using larger SDS. According to the experimental results, in the liquid phantom and single-layer solid phantoms experiments, there are very high linearity between the experimental and the simulated (R2 are above 0.99), and the spectral error between the calibrated experimental spectra and simulated spectra are small. Feasibility was validated on a three-layered solid phantom with errors in extracted optical coefficients below 15%. Finally, the prefrontal area of the human head was measured and scattering and absorption coefficients of each layer were extracted by iterative spectral fitting to Monte Carlo simulation results. Optical properties extracted from in-vivo measurements fell within reasonable ranges of reported values. In contrast to ex-vivo measurements, the presented procedure enables the reconstruction of distributions of absorption changes in the cortex using subject’s own optical properties. | en |
dc.description.provenance | Made available in DSpace on 2021-07-11T15:38:33Z (GMT). No. of bitstreams: 1 ntu-107-R05945032-1.pdf: 3618093 bytes, checksum: a32c98a3fb8c27c077a1019d04ed9c67 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 口試委員審定書 ................................................................................................................I
致謝 ...................................................................................................................................II 中文 摘要 .........................................................................................................................III Abstract...........................................................................................................................IV 目錄 .................................................................................................................................VI 圖目錄 ..........................................................................................................................VIII 表目錄 ..............................................................................................................................X 第一章 緒論 1.1 前言 ...................................................................................................................1 1.2 研究動機 ...........................................................................................................2 1.3 文獻回顧與探討 ...............................................................................................3 1.4 研究問題與具體目標 .......................................................................................5 1.4.1 研究問題 .................................................................................................5 1.4.2 具體目標 .................................................................................................5 第二章 技術理論介紹 技術理論介紹 2.1 人體頭部組織結構 ...........................................................................................6 2.2 漫反射之擴散方程理論 ...................................................................................9 2.3 蒙地卡羅演算法 .............................................................................................12 2.3.1 光子在組織傳播方式 ...........................................................................12 2.3.2 組織模型 ...............................................................................................16 第三章 研究方法及步驟 研究方法及步驟 3.1 研究流程 ..........................................................................................................21 3.2 光學系統介紹 ..................................................................................................22 3.2.1 近紅外 光譜系統 ...................................................................................22 3.2.2 光纖探頭設計 .......................................................................................23 3.3 光譜系統校正流程 ..........................................................................................30 3.3.1 固態仿體實驗 ........................................................................................30 3.3.2 液態仿體實驗 ........................................................................................34 3.4 逆向光譜擬合工具 ..........................................................................................35 3.5 正常人體頭部實驗 ..........................................................................................37 第四章 實驗結果與討論 實驗結果與討論 4.1 光學系統分析 .................................................................................................41 4.1.1 光譜解析度量測 ..................................................................................41 4.1.2 系統穩定性探討 ..................................................................................43 4.2 仿體量測結果 .................................................................................................46 4.2.1 液態仿體量測結果 ...............................................................................46 4.2.2 單層固態仿體量測結果 .......................................................................48 4.2.3 多層固態仿體 量測結果...............................................................51 4.3 光學參數分析 .................................................................................................54 4.3.1 定量多層固態仿體之各光學參數結果 ...........................................54 4.3.2 定量正常人體頭部組織之各層光學參數結果 ...................................57 第五章 結論與未來展望 結論與未來展望 5.1 結論 ................................................................................................................. 66 5.2 未來展望 ..........................................................................................................67 參考文 獻.........................................................................................................................68 | |
dc.language.iso | zh-TW | |
dc.title | 以近紅外光譜系統定量仿體及人體頭部組織光學參數 | zh_TW |
dc.title | Construction of Near-infrared Spectroscopy System for
Quantifying Optical Properties of Phantoms and In-vivo Human Head Tissues | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陳右穎(You-Yin Chen),盧家鋒(Chia-Feng Lu) | |
dc.subject.keyword | 近紅外光譜技術,擴散光學斷層影像,吸收係數,散射係數,組織模型, | zh_TW |
dc.subject.keyword | Near-infrared spectroscopy (NIRS),Diffuse optical tomography (DOT),absorption coefficient,scattering coefficient,tissue model, | en |
dc.relation.page | 71 | |
dc.identifier.doi | 10.6342/NTU201803245 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2018-08-14 | |
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 |
dc.date.embargo-lift | 2023-08-21 | - |
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-107-R05945032-1.pdf 目前未授權公開取用 | 3.53 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。