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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 李百祺(Pai-Chi Li) | |
dc.contributor.author | Rou-Xuan Huang | en |
dc.contributor.author | 黃柔軒 | zh_TW |
dc.date.accessioned | 2021-06-17T04:27:06Z | - |
dc.date.available | 2023-08-18 | |
dc.date.copyright | 2018-08-18 | |
dc.date.issued | 2018 | |
dc.date.submitted | 2018-08-13 | |
dc.identifier.citation | [ 1 ] Spranger, S., Dai D., Horton B., Gajewski T. F. (2017). Tumor-Residing Batf3 Dendritic Cells Are Required for Effector T Cell Trafficking and Adoptive T Cell Therapy. Cancer Cell, 31(5), 614-615.
[ 2 ] Houot, R., Schultz, L. M., Marabelle, A., Kohrt, H. (2015). T-cell-based Immunotherapy: Adoptive Cell Transfer and Checkpoint Inhibition. Cancer Immunology at the Crossroads, 3(10), 1115-1122. [ 3 ] von Andrian U. H., Mackay, C. R. (2000). T-Cell Function and Migration — Two Sides of the Same Coin. The New England Journal of Medicine, 343(14), 1020-1034. [ 4 ] Balkwill , F. (2004). Cancer and the chemokine network. Nature Reviews Cancer, 4(7), 540-550. [ 5 ] Edmondson, R., Broglie, J. J., Adcock, A. F. and Yang, L. (2014). Three-Dimensional Cell Culture Systems and Their Applications in Drug Discovery and Cell-Based Biosensors Assay and Drug Development Technologies, 12(4), 207-218. [ 6 ] Marianne Lintz, Adam Muñoz and Cynthia A. Reinhart-King. (2017). The Mechanics of Single Cell and Collective Migration of Tumor Cells. Journal of Biomechanical Engineering ,139(2), 021005. [ 7 ] Hazan, R. B., Phillips, G. R., Qiao, R. F., Norton, L., Aaronson, S. A. (2000). Exogenous Expression of N-Cadherin in Breast Cancer Cells Induces Cell Migration, Invasion, and Metastasis. Journal of cell biology, 148 (4), 779-790. [ 8 ] Paddock S. W. (2000). Principles and Practices of Laser Scanning Confocal Microscopy. Molecular Biotechnology, 16(2), 127-149. [ 9 ] Bougherar, H., et al. (2015). Real-time imaging of resident T cells in human lung and ovarian carcinomas reveals how different tumor microenvironments control T lymphocyte migration. Frontiers in Immunology, 12(6), 1-12. [ 10 ] Oheim, M., Michael, D. J., Geisbauer, M., Madsen, D., Chow, R. H. (2006). Principles of two-photon excitation fluorescence microscopy and other nonlinear imaging approaches. Advanced Drug Delivery Reviews, 58, 788–808. [ 11 ] Miller, M. J., Wei, S. H., Parker, I., Cahalan, M. D. (2002). Two-photon imaging of lymphocyte motility and antigen response in intact lymph node. Science, 296(5574), 1869-1873. [ 12 ] Kruger, R. (1994). Photoacoustic ultrasound. Medical physics, 21(7), 127-131. [ 13 ] Song, H., Wang, L. V. (2010). Neurovascular photoacoustic tomography. Front Neuroenergetics, 2(10), 1-7. [ 14 ] Li, G., Xia, J., Maslov, K., et al. (2015). Tripling the detection view of high-frequency linear-array-based photoacoustic computed tomography by using two planar acoustic reflectors. Quant Imaging Med Surg, 5(1), 57–62. [ 15 ] Zhang, H. F., Maslov, K., Stoica, G., Wang, L. V. (2006). Functional photoacoustic microscopy for high-resolution and noninvasive in vivo imaging. Nature biotechnology, 24(7), 848-851. [ 16 ] Maslov, K., Zhang, H. F., Wang, L. V. (2008). Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries. Optics Letters, 33(9), 929–931. [ 17 ] Yang, S., Ye, F., Xing, Da. Strohm, E. M., Moore, M. J., Kolios, M. C. (2016). Single Cell Photoacoustic Microscopy: A Review. IEEE journal of selected topics in quantum electronics, 22(3), 6801215. [ 18 ] Yao, J., Wang, L. V. (2013). Photoacoustic microscopy. Laser Photonics, 7(5), 758–778. [ 19 ] Hu, S., Maslov, K., Wang, L. V. (2011). Second-generation optical-resolution photoacoustic microscopy with improved sensitivity and speed. Optics letters, 36(7), 1134-1136. [ 20 ] Topaloglu, N., Gulsoy, M., Yuksel, S. (2013). Antimicrobial Photodynamic Therapy of Resistant Bacterial Strains by Indocyanine Green and 809-nm Diode Laser. Photomedicine and laser surgery, 31(4), 155–162. [ 21 ] Chen, Y. S., Frey, W., Kim, S., et al. (2011). Silica-Coated Gold Nanorods as Photoacoustic Signal Nanoamplifiers. Nano Letters, 11(2), 348–354. [ 22 ] Wei, C. W., Chen, L. C., Souris, J. S., et al. (2010). Enhanced photoacoustic stability of gold nanorods by silica matrix confinement. Journal of Biomedical Optics, 15(1), 016010. [ 23 ] Candès,E. J., Romberg, J., Tao, T. (2006). Robust uncertainty principles:exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory, 52(2), 489–509. [ 24 ] Pan, J. S., Li,W., Yang, C. S., Yan, L. J. (2015). Image steganography based on subsampling and compressed sensing. Multimedia Tools and Applications, 74(21), 9191–9205. [ 25 ] Candès,E. J. (2008). The restricted isometry property and its implications for compressed sensing. Theory of Signals/Mathematical Analysis, 346(9), 589-592. [ 26 ] Candès, J., Recht, B. (2009). Exact Matrix Completion via Convex Optimization. Foundations of Computational Mathematics, 9(6), 717–772. [ 27 ] Candès, E. J., Tao, T. (2010). The power of convex relaxation: Near-optimal matrix completion. IEEE Transactions on Information Theory, 56(5), 2053-2080. [ 28 ] Candès, J., Plan, Y. (2009). Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements. IEEE Transactions on Information Theory, 57(4), 2342-2359. [ 29 ] Provost, J., Lesage, F. (2009). The Application of Compressed Sensing for Photo-Acoustic Tomography. IEEE Transactions On Medical Imaging, 28(4), 585-594. [ 30 ] Liang, D., Zhang, H. F. and Ying, L. (2009). Compressed sensing photoacoustic imaging based on random optical illumination. International Journal of Functional Informatics and Personalised Medicine, 2, 394-406. [ 31 ] Guo, Z., Li, C., Song, L., Wang, L. V. (2010). Compressed sensing in photoacoustic tomography in vivo. Journal of Biomedical Optics ,15(2), 021311. [ 32 ] Xia, J., Li, G., Wang, L. V., et al. (2013). Wide-field two-dimensional multifocal optical-resolution photoacoustic-computed microscopy. Optics letters, 38(24), 5236-5239. [ 33 ] Cai, J. F., Candès, J., Shen, Z. (2008). A Singular Value Thresholding Algorithm for Matrix Completion. SIAM Journal on Optimization and Control, 20(4), 1956–1982. [ 34 ] Liu, T., Sun, M. J., Meng, J., et al. (2016). Compressive Sampling Photoacoustic Microscope System based on Low Rank Matrix Completion. Biomedical Signal Processing and Control, 26, 58–63. [ 35 ] Yao, J., Wang, L. V. (2014). Sensitivity of photoacoustic microscopy. Photoacoustics, 2(2), 87-101. [ 36 ] Meijering, E., Dzyubachyk, O., Smal, I. (2012). Methods for Cell and Particle Tracking. Imaging and Spectroscopic Analysis of Living Cells, 504(9), 183-200. [ 37 ] Banitalebi, B., Amiri, H. (2008). An Improved Nearest Neighbor Data Association Method for Underwater Multi-Target Tracking. IEEE workshop & exhibition on new trends for environmental monitoring using passive systems, 1–4. [ 38 ] Meijering, E. (2012). Cell Segmentation: 50 Years Down the Road. IEEE Signal Processing Magazine, 29(5),140–145. [ 39 ] James , R. E., Kim, Y., Hockberger , P., Szele , F. G. (2011). Subventricular Zone Cell Migration: Lessons from Quantitative Two-Photon Microscopy. Frontiers in Neuroscience, 5(30), 1-11. [ 40 ] Du, K., Ko, S. H., Gallatin, G. M. (2012). Quantum dot-DNA origami binding: a single particle, 3D, real-time tracking study. Chemical Communications, 49, 907-909. [ 41 ] Yao, J., Wang, L., Yang, J. M. (2015). High-speed label-free functional photoacoustic microscopy of mouse brain in action. Nature Methods, 12, 407–410. [ 42 ] Song, L., Maslov K., Wang, L. V. (2008). Fast 3-D dark-field reflection-mode photoacoustic microscopy in vivo with a 30-MHz ultrasound linear array. Journal of Biomedical Optics, 13(5), 054028. [ 43 ] Song, L., Maslov K., Wang, L. V. (2010). Section-illumination photoacoustic microscopy for dynamic 3-D imaging of microcirculation in vivo. Optics Letters, 35(9), 1482–1484. [ 44 ] Li, L., Zhang, W., Wang, J. (2016). A viscoelastic–stochastic model of the effects of cytoskeleton remodelling on cell adhesion. Journal of the Royal Society Interface, 3(10), 1-15. [ 45 ] Bennett, M., Cantini, M., Reboud,J., et al. (2018). Molecular clutch drives cell response to surface viscosity. Proceedings of the National Academy of Sciences of the United States of America, 115(6), 1192–1197. [ 46 ] Lewis, O. L., Zhang, S., Guy, R. D., del Álamo, J. C. (2015). Coordination of contractility, adhesion and flow in migrating Physarum amoebae. Journal of the Royal Society Interface, 12(106), 1-12. [ 47 ] Chen, B., Estrada, L. C., Hellriege, C., Gratton E. (2011). Nanometer-scale optical imaging of collagen fibers using gold nanoparticles. Biomedical Optics Express, 2(3), 511-519. [ 48 ] He, Y., Wang, L., Shi, J., et al. (2016). In vivo label-free photoacoustic flow cytography and on-the-spot laser killing of single circulating melanoma cells. Scientific Reports, 6, 39616. [ 49 ] Pitsillides, C. M., Joe, E. K., Wei, X., Anderson, R. R., Lin, C. P. (2003). Selective Cell Targeting with Light-Absorbing Microparticles and Nanoparticles. Biophysical Journal, 84(6), 4023–4032. [ 50 ] Shi, Y., Qin, H., Yang, S., Xing D. (2016). Thermally confined shell coating amplifies the photoacoustic conversion efficiency of nanoprobes. Nano Research, 9(12), 3644–3655. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/70388 | - |
dc.description.abstract | 監測T細胞與腫瘤的動態交互作用有助於了解癌症免疫治療的機制。使用光學解析度光聲顯微系統來進行此類監測,不僅能提供足夠之空間解析度,也能比傳統光學顯微鏡提供較深的穿透深度。藉由外源性對比劑,此雙波長光聲顯微鏡能同時藉由523 nm雷射觀測以包矽奈米金球標定的胞殺性T細胞,並藉由800 nm雷射觀測以ICG螢光染劑標定的肝癌細胞之分布。然而,為達到足夠觀測單一細胞之空間取樣,在雷射PRF為1 kHz的情況下進行160 × 160 × 150 μm3的三維掃描範圍約需要20分鐘。為了進一步提高成像速率以有效進行細胞追蹤,我們提出一隨機稀疏取樣機制實現快速稀疏光聲數據之採集,影像重建方法則為基於壓縮感知理論下的低秩矩陣填充,透過最小核範數最佳化問題得以從顯著減少的取樣中重建回近似全取樣的高品質影像。就目前實驗結果發現光聲反應過程中的熱膨脹可能伴隨生物效應,使得細胞活性受到影響,因此仍未能追蹤細胞的動態移動。我們透過此基於壓縮感知的雙波長光學解析度光聲顯微鏡,以較高的時間解析度觀測三維腫瘤微環境中T細胞的分布,當取樣密度為0.5此系統可以減少40%的數據採集時間。一旦克服光聲轉換伴隨的生物效應,此系統即成為在三維細胞培養系統中觀測細胞追蹤的有利工具,極具潛力應用於臨床前研究以了解細胞的動態行為。 | zh_TW |
dc.description.abstract | Observing interactions between T cells and tumor is important for understanding cancer immunotherapy. Optical-resolution photoacoustic microscopy (OR-PAM) can provide not only high spatial resolution but also deeper penetration than conventional optical microscopy, which makes it appropriate for such observations. With appropriate molecular probes, the dual-wavelength OR-PAM can be used to map the distribution of CD8+ cytotoxic T lymphocytes (CTLs) labeled with silica coated gold nanospheres (Si-AuNS) under 523 nm laser irradiation. Likewise, Hepta1-6 tumor spheres can be labelled with indocyanine green (ICG) for 800 nm laser irradiation. Nonetheless, to achieve sufficient spatial sampling for single cells, it takes approximately 20 minutes to scan a volume of 160 × 160 × 150 μm3 at 1 kHz laser PRF. In order to increase the imaging speed for dynamic T cell tracking, we propose a random sparse sampling mechanism to achieve fast sparse photoacoustic data acquisition. With the sparse sampling, the image reconstruction is formulated as low-rank matrix completion based on the compressed sensing (CS) theory. We show that reliable reconstruction can be achieved via nuclear-norm minimization optimization so image quality can be obtained from significantly fewer measurements. Current experimental results reveal that thermal expansion of photoacoustic generation may affect cell viability, which may be a main reason why we have not been able to track cell migration. In conclusion, we use the dual-wavelength OR-PAM with CS to visualize T cell distribution in a 3D tumor microenvironment with higher temporal resolution. Data acquisition time can be reduced by 40% when the sampling density is 0.5. The system can be a valuable tool for evaluating cell tracking in an in vitro 3D cell culture system, once the bioeffects of photoacoustic transformation are overcome. The imaging system is potentially important for preclinical research to understand dynamic cellular behavior. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T04:27:06Z (GMT). No. of bitstreams: 1 ntu-107-R05945014-1.pdf: 6326181 bytes, checksum: 3bb9ffbe3ef0e6b4ef8632a81bde5d29 (MD5) Previous issue date: 2018 | en |
dc.description.tableofcontents | 口試委員會審定書 I
誌謝 II 摘要 III Abstract IV 目錄 VI 圖目錄 X 表目錄 XIII 第一章 緒論 1 1.1 研究背景 1 1.1.1 三維細胞培養系統 2 1.1.2 細胞追蹤技術 3 1.2 光聲成像系統簡介 7 1.2.1 光聲斷層成像 9 1.2.2 光聲顯微成像 9 1.2.3 光聲對比劑 10 1.3 壓縮感知理論及其研究 13 1.3.1 低秩矩陣填充理論 15 1.3.2 基於壓縮感知之光聲成像系統研究 16 1.4 研究動機與目的 18 1.5 本文架構 19 第二章 壓縮雙波長光聲分子顯微鏡 20 2.1 雙波長光學解析度光學顯微鏡系統架構 20 2.2 雷射掃描模式 21 2.2.1 二維振鏡掃描機制 21 2.2.2 全取樣與稀疏取樣模板 22 2.2.3 三維光聲掃描 23 2.3 空間解析度 24 2.4 三維掃描追蹤速度 27 2.5 系統成像資料擷取時間 28 第三章 低秩矩陣填充重建與細胞追蹤模擬 29 3.1 低秩矩陣填充最佳化演算法 29 3.1.1 稀疏光聲顯微影像的低秩填充模型 33 3.1.2 評估重建結果的影像品質指標 34 3.1.3 稀疏光聲顯微影像的重建模擬結果 36 3.2 細胞追蹤 38 3.2.1 細胞軌跡追蹤演算法 39 3.2.2 基於慣性假設之最近鄰居法 40 3.2.3 細胞軌跡追蹤模擬結果 41 第四章 細胞光聲顯微影像 43 4.1 以外源性光聲對比劑標定T細胞之光聲影像 43 4.1.1 奈米金球-T細胞 43 4.1.2 包矽奈米金球-T細胞 45 4.1.3 靛氰綠-T細胞 46 4.2 以外源性光聲對比劑標定腫瘤球之光聲影像 46 4.2.1 靛氰綠-腫瘤球 47 4.2.2 奈米金球-腫瘤球 48 4.3 雙細胞混合分布之光聲影像 49 4.4 稀疏取樣實驗結果 49 4.5 經雙向濾波器提升重建影像品質 51 4.6 激發光聲訊號後的T細胞型態 53 第五章 問題與討論 54 5.1 包矽奈米金球光聲轉換的探討 54 5.2 光聲細胞實驗所遇到的困難 55 5.2.1 雷射光通量 57 5.2.2 光聲轉換的熱能影響 57 5.3 提升系統成像速度方法 58 5.4 系統追蹤速度的探討 59 5.5 SVT與ADMM演算法比較 60 第六章 結論與未來工作 61 6.1 結論 61 6.2 未來工作 61 6.2.1 驗證光聲轉換對細胞活性的影響 61 6.2.2 以提升矽層厚度的包矽奈米金球標定T細胞 62 6.2.3 追蹤T細胞移動軌跡 62 6.2.4 基於壓縮感知的OR-PAM實踐 64 6.2.5 應用稀疏取樣於細胞實驗的重建比較 64 6.2.6 非均勻性稀疏取樣區域的選取 64 6.2.7 架設空間濾波器優化雷射光分布 64 6.2.8 以雙波長光聲顯微系統研究細胞追蹤之應用 65 參考文獻 66 | |
dc.language.iso | zh-TW | |
dc.title | 使用壓縮感知之雙波長光聲顯微技術及其於三維細胞追蹤之應用 | zh_TW |
dc.title | Dual-wavelength OR-PAM with compressed sensing for cell tracking in 3D cell culture systems | en |
dc.type | Thesis | |
dc.date.schoolyear | 106-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 宋孔彬(Kung-Bin Sung),謝寶育(Bao-Yu Hsieh) | |
dc.subject.keyword | 光聲顯微鏡,三維細胞培養系統,壓縮感知,低秩矩陣填充,細胞追蹤, | zh_TW |
dc.subject.keyword | Photoacoustic microscopy,3D cell culture systems,compressed sensing,low rank matrix completion,cell tracking, | en |
dc.relation.page | 69 | |
dc.identifier.doi | 10.6342/NTU201803262 | |
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 |
顯示於系所單位: | 生醫電子與資訊學研究所 |
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