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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50995完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 宋孔彬 | |
| dc.contributor.author | Yu-Ming Lai | en |
| dc.contributor.author | 賴鈺銘 | zh_TW |
| dc.date.accessioned | 2021-06-15T13:11:24Z | - |
| dc.date.available | 2017-07-04 | |
| dc.date.copyright | 2016-07-04 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-06-24 | |
| dc.identifier.citation | [1] Ferrari M Quaresima V.” A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application,” Neuroimage. 2012 Nov 1;63(2):921-35. doi: 10.1016
[2] Lloyd-Fox S, Blasi A, Elwell CE. Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy. Neuroscience & Biobehavioral Reviews. 2010; 34:269–284. [3] Gibson AP, Austin T, Everdell NL, Schweiger M, Arridge SR, Meek JH, Wyatt JS, Delpy DT, Hebden JC. Three-dimensional whole-head optical tomography of passive motor evoked responses in the neonate. Neuroimage. 2006 [4] Durduran T, Choe R, Baker WB, Yodh AG. Diffuse optics for tissue monitoring and tomography. Rep Prog Phys. 2010; 73:076701. [5] Jobsis FF. Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science. 1977; 198:1264–7. [6] B. Crosson, A. Ford, K. M. McGregor, M. Meinzer, S. Cheshkov, X. Li, 'Functional imaging and related techniques: An introduction for rehabilitation researchers,' Journal of rehabilitation research and development, vol. 47, p. vii, 2010. [7] F. Irani, S. M. Platek, S. Bunce, A. C. Ruocco, and D. Chute, 'Functional near infrared spectroscopy (fNIRS): an emerging neuroimaging technology with important applications for the study of brain disorders,' Clin Neuropsychol, vol. 21, pp. 9-37, Jan 2007. [8] Ogawa, S., Lee, T.M., Kay, A.R., Tank, D.W. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl. Acad. Sci. U. S. A., 1990, 87, 9868–9872 [9] Bandettini, P.A., Wong, E.C., Hinks, R.S., Tikofsky, R.S., Hyde, J.S. Time course EPI of human brain function during task activation. Magn. Reson. Med. 25, 1992, 390–397. [10] Kawaguchi, F., Yamashita, Y., Ito, Y., Maki, A., Takeuchi, H., 1991. Near infrared optical CT image of rat brain. Med. Biol. Eng. Comput. 29 (Suppl. 2), 959. [11] Ogawa, S., Tank, D.W., Menon, R., Ellermann, J.M., Kim, S.G., Merkle, H., Ugurbil, K. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc. Natl. Acad. Sci. U. S. A. 89,(1992), 5951–5955. [12] Durduran, T., Choe, R., Bake, W.B., Yodh, A.G. Diffuse optics for tissue monitoring and tomography. Rep. Prog. Phys. 73, (2010), 076701. [13] Fenghua Tian, Depth-compensated diffuse optical tomography enhanced by general linear model analysis and an anatomical atlas of human head. NeuroImage 85 (2014) 166–180 [14] Harsimrat Singha.' Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study. NeuroImage: Clinical 5 (2014) 256–265. [15] Adam T. Eggebrecht, ,“Mapping distributed brain function and networkswith diffuse optical tomography”. Nature Photonics vol 8, June 2014 P448-454. [16] RJ Cooper, M Caffini, J Dubb, Q Fang, A Custo wt al. Validating atlas-guided DOT: a comparison of diffuse optical tomography informed by atlas and subject-specific anatomies.” Neuroimage. 2012 September ; 62(3) [17] Boas DA, Dale AM. “Simulation study of magnetic resonance imaging-guided cortically constrained diffuse optical tomography of human brain function.” Appl Opt. 2005; 44:1957–1968. [18] Custo A, Boas DA, Tsuzuki D, Dan I, Mesquita R, Fischl B, Grimson WEL, Wells W III. Anatomical atlas-guided diffuse optical tomography of brain activation. NeuroImage. 2010; 49:561–567. [19] Gentaro Taga, Fumitaka Homae, and Hama Watanabeb. “Effects of source-detector distance of near infrared spectroscopy onthe measurement of the cortical hemodynamic response in infants.” NeuroImage 38 (2007) 452–460 [20] S. Prahl, “Optical Absorption of Hemoglobin” (1999), http://omlc.ogi.edu/spectra/hemoglobin/ . [21] Delpy, D.T., Cope, M., van der Zee, P., Arridge, S., Wray, S., Wyatt, J. Estimation of optical pathlength through tissue from direct time of flight measurement. Phys. Med. Biol. 33 (12) (1988), 1433. [22] Ayaz, H., Shewokis, P. A., Curtin, A. 'Using MazeSuite and Functional Near Infrared Spectroscopy to Study Learning in Spatial Navigation'. Journal of Visualized Experiments (56). (2011). [23] Tikhonov, A. “Solution of incorrectly formulated problems and the regularization method.” Sov. Math. Dokl. 4 (1963), 1035–1038. [24] Metropolis N., Ulam, S. “The Monte Carlo Method” Journal of the American Statistical Association 44 (247) (1949): 335–341. [25] SA Prahl, M Keijzer, SL Jacques, AJ Welch “A Monte Carlo model of light propagation in tissue” PIE Institute Series Vol. IS 5 (1989): 102-111 [26] Gary E. Strangman , Zhi Li, Quan Zhang “Depth Sensitivity and Source-Detector Separations for Near Infrared Spectroscopy Based on the Colin27 Brain Template2002 Feb 11;10(3):159-70. [27] Boas D, Culver J, Stott J, Dunn A. “Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head.” PLoS One. 2013; 8(8): e66319. [28] CM Aasted, MA Yücel, RJ Cooper.”Anatomical guidance for functional near-infrared spectroscopy AtlasViewer tutorial” Neurophotonics 2(2), 020801 (Apr–Jun 2015) [29] D. L. Collins, “Design and construction of a realistic digital brain phantom,” IEEE Trans. Med. Imaging 17(3), 463–468 (1998). [30] D. Boas, “Three dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head,” Opt. Express 10(3), 159–170 (2002). [31] Sobanawartiny Wijeakumar, John P. Spencer, Kevin Bohache, David A. Boas, Vincent A. Magnotta, “Validating a new methodology for optical probe design and image registration in fNIRS studies” Neuroimage. 2015 Feb 1;106:86-100. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50995 | - |
| dc.description.abstract | 功能性近紅外線光譜技術(fNIR, Functional near-infrared spectroscopy)發展相當快速,能在開放空間使用,是其他種腦部的神經影像學無法達成的。現今無論是在硬體上或演算法上,都有相當多的進展,但是卻較少有探頭擺放的研究。探頭擺放對於重建同樣也有重大的影響。
本研究試著解決研究近紅外線光譜技術中,光源與探測器,究竟要如何選擇排列,才能使整個系統的靈敏度上升。先以使用了幾何學中的鑲嵌問題,將重心放光源,頂點放探測器,推導出多種的探頭幾何擺放方法。接著,使其產生有2.9公分的通道,符合模擬用模型的最佳的光源-探測器間距。在特性分析方面,提出四個特性分析的指標─每一平方公分裡會有幾個通道、每一個探頭平均控制幾平方公分、每一個探頭平均創造了幾個有效通道、共有幾組不同的光源-探測器間距。並根據指標,發展了探頭擺放方法的抉擇流程。此流程的正確性,已透過AtlasViewer模擬軟體來驗證。 依照密度做結論,一般性的擺法選擇如下:低密度時選擇截半六邊形鑲嵌產生的排列方法,並讓光源-探測器間距為2.9公分,兩光源間距5.8公分的擺法。中密度選擇畢達哥拉斯平鋪產生的排列方法,並讓光源-探測器間距為2.05公分,兩光源間距4.58公分的擺法。高密度一樣選擇畢達哥拉斯平鋪產生的排列方法,讓光源-探測器間距為1.45公分,兩光源間距3.24公分的擺法。最後是超高密度,選擇正方形鑲嵌,並讓光源-探測器間距為1.3公分,兩光源間距1.83公分的擺法。 有了上述的結論與抉擇流程,往後使用功能性近紅外線光譜技術,探頭擺放方式就可以有一定的規則可循,也能針對各自適合的方向去做選擇。如此測量到資訊會更有用,進行重建的效果也會更好。期許未來能開發可自動分析的程式,依循此研究的方法與結論,創造出符合複合式的擺法。 | zh_TW |
| dc.description.abstract | Functional near-infrared spectroscopy (fNIR,) technic has developed rapidly recent year. fNIR can use in open-environment which no other neuroimaging can use in. Hardware and algorithm is progressing in fNIR, but optode placement, which also cause significant influence in reconstruction, is researched less.
This research try to solve the problem how source and detector placement in fNIR can improve the sensitivity. First, using well-known tessellation in geometry to derivate the geometry of optode placement. Then, let one of the channel in optode placement become 2.9 cm, which is the best source-detector separation (SDS) in brain model. After that, we provide 4 characteristics─ channels per cm2, optodes controlled per cm2, channels per optode and kinds of SDSs─ to analysis the performance of optode placement. Following the characteristics, we development a progress to select the placement. It is the correctness of the progress that is proved by AtlasViewer simulation program. To sum up, in the density of optode opinion, hexagonal placement with SDS 2.9 cm, source separation(SS) 5.8 cm is the best in low density. Square placement with SDS 2.05 cm, SS 4.5 cm is the best in medium density. In high density, square placement with SDS 1.45 cm, SS 324 cm is the best. Square placement with SDS 1.3 cm, SS 1.83 cm is the best in super high density. By summarizing the process and the conclusion, we can follow the rule in optode placement and modify by user preference. As a result, the signal in fNIR is stronger, and the performance of reconstruction is better. In future, an automatic analysis program with the progress is needing to development new combined placement. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T13:11:24Z (GMT). No. of bitstreams: 1 ntu-105-R03945008-1.pdf: 2190137 bytes, checksum: b496a5e7eab2d1aa96f36e03d3ee6a90 (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
致謝 ii 中文摘要 iii ABSTRACT iv CONTENTS v 圖目錄 vii 表目錄 x Chapter 1 緒論 1 Chapter 2 文獻探討 3 2.1 探頭擺法文獻探討 3 2.2 技術理論介紹 6 2.2.1 功能性近紅外線光譜技術 6 2.2.2 蒙地卡羅演算法 9 Chapter 3 研究方法 11 3.1 探頭幾何擺放的選擇 11 3.2 光源-探測器間距決定 15 3.3 探頭擺放的特性分析 17 3.4 以AtlasViewer進行模擬驗證 19 Chapter 4 結果與討論 24 4.1 探頭擺放的幾何形狀 24 4.2 光源-探測器間距與有效通道 26 4.3 使用特性分析表來抉擇探頭擺放方法 28 4.3.1 特性分析表結果 28 4.3.2 探頭擺放方法之抉擇 33 4.4 AtlasViewer的模擬驗證 35 Chapter 5 結論與未來展望 45 Chapter 6 參考文獻 46 | |
| dc.language.iso | zh-TW | |
| dc.subject | 探頭擺放 | zh_TW |
| dc.subject | 功能性近紅外線光譜技術 | zh_TW |
| dc.subject | 探頭擺放 | zh_TW |
| dc.subject | 腦 | zh_TW |
| dc.subject | 功能性近紅外線光譜技術 | zh_TW |
| dc.subject | 腦 | zh_TW |
| dc.subject | Functional near-infrared spectroscopy | en |
| dc.subject | Functional near-infrared spectroscopy | en |
| dc.subject | Brain | en |
| dc.subject | Optode placement | en |
| dc.subject | AtlasViewer | en |
| dc.subject | Brain | en |
| dc.subject | Optode placement | en |
| dc.subject | AtlasViewer | en |
| dc.title | 功能性近紅外線光譜技術中探頭擺放決策的模擬研究 | zh_TW |
| dc.title | A Simulation Study of Optode Placement in Functional Near Infrared Spectroscopy | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 盧家鋒,蘇國棟 | |
| dc.subject.keyword | 功能性近紅外線光譜技術,腦,探頭擺放, | zh_TW |
| dc.subject.keyword | Functional near-infrared spectroscopy,Brain,Optode placement,AtlasViewer, | en |
| dc.relation.page | 49 | |
| dc.identifier.doi | 10.6342/NTU201600486 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-06-26 | |
| 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 | |
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