臺灣博碩士論文加值系統

血流流速是一評估健康程度的重要指標，而光聲顯微鏡(Photoacoustic Microscopy)為量測活體內血管影像及血流流速之新興工具。光聲顯微鏡之測量訊號的方法:使用脈衝雷射加熱目標物，如紅血球等，因此，相較於傳統之光學顯微鏡，光聲顯微鏡顯然較適合用於活體內觀測。目前文獻中基於光學解析度光聲顯微鏡的流速演算法僅能估算軸向或是橫向單一方向流速，且光聲訊號具有寬頻且無中心頻率的特性，使用傳統運用在M-mode下的都卜勒軸向流速演算法，或是在時域上的使用其正交相行交相關的演算法等皆不適合。在本論文中，我們針對光學解析度光聲顯微鏡光聲訊號的特性，提出了使用蝶狀搜尋(Buttefly Search)之光聲血流流速估計演算法，可同時量測軸向、橫向流速及都卜勒流速方向。透過依據光學解析度光聲訊號數學模型模擬的M-mode訊號來驗證所提出演算法的可行性，並與目前主要的橫向流速以及軸向流速演算法分別比較。此外，我們亦探討包括雷射、超音波探頭等系統端的選擇對所提出流速演算法之影響以及驗證了演算法的抗雜訊能力。

In the litereature, flow estimation algorithms for optical resolution photoacoustic microscopy (ORPAM) only provide single-axis flow velocity estimation – either lateral or axial velocity estimation. In this study, according to the charcteristics of ORPAM photoacoustic flow signals, we propose a novel photoacoustic flow estimation algorithm using the butterfly search technique which allows the simultaneous estimation of both axial flow velocity and lateral flow rate. Here, the feasibility of the proposed method is verified via the M-mode simulation based on OR-PAM photoacoustic signal model, and the performance of the proposed method is compared with that of the conventional axial and lateral velocity estimators. The influence of the ORPAM system parameters such as the number of laser pulses and types of the ultrasound transducers on the performance of the proposed method is also discussed. In addition, the insusceptibility of the proposed method to the noise is also demonstrated.

中文摘要 ii
Abstract iii
圖目錄 vi
表目錄 xi
第1章 緒論 1
1.1 光學解析度光聲顯微鏡之流速演算法簡介 1
1.1.1 橫向流速演算法 3
1.1.2 軸向流速演算法 7
1.2 研究動機與目的 8
1.3 論文架構 9
第2章 使用蝶狀搜尋之光聲血流流速估計演算法 10
2.1蝶狀搜尋演算法 10
2.2演算法實現步驟 13
第3章 模擬結果與討論 20
3.1訊號模擬方法 20
3.1.1 模型概觀 20
3.1.2 空間脈衝效應 22
3.1.3 電氣脈衝效應 25
3.1.4 雷射光束 27
3.1.5 N型波 28
3.2 模擬結果 30
3.2.1 空間脈衝效應 32
3.2.2 電氣脈衝效應 41
3.2.3 流速角度影響 47
3.2.4 脈衝重複頻率以及雷射發數 51
3.2.5 雜訊影響 56
第4章 結論及未來工作 61
4.1 結論 61
4.2 未來工作 63
參考文獻 65

[1] Iadecola, C. (2004). Neurovascular regulation in the normal brain and in Alzheimer's disease. Nature Reviews Neuroscience, 5(5), 347-360.

[2] Zlokovic, B. V. (2010). Neurodegeneration and the neurovascular unit. Nature medicine, 16(12), 1370-1371.

[3] Baker, W. B., Sun, Z., Hiraki, T., Putt, M. E., Durduran, T., Reivich, M., &; Greenberg, J. H. (2013). Neurovascular coupling varies with level of global cerebral ischemia in a rat model. Journal of Cerebral Blood Flow &; Metabolism,33(1), 97-105.

[4] Liao, L. D., Tsytsarev, V., Delgado-Martínez, I., Li, M. L., Erzurumlu, R., Vipin, A., ... &; Thakor, N. V. (2013). Neurovascular coupling: in vivo optical techniques for functional brain imaging. Biomed Eng Online, 12, 38.

[5] Maslov, K., Zhang, H. F., Hu, S., &; Wang, L. V. (2008). Optical-resolution photoacoustic microscopy for in vivo imaging of single capillaries.Optics letters, 33(9), 929-931.

[6] Yao, J., Maslov, K. I., Zhang, Y., Xia, Y., &; Wang, L. V. (2011). Label-free oxygen-metabolic photoacoustic microscopy in vivo. Journal of biomedical optics, 16(7), 076003-076003.

[7] Fang, H., &; Wang, L. V. (2009)., M-mode photoacoustic particle flow .imaging. Optics letters, 34(5), 671-673.


[8] Chen, S. L., Xie, Z., Carson, P. L., Wang, X., &; Guo, L. J. (2012, February). Photoacoustic correlation spectroscopy for in vivo blood flow speed measurement. In SPIE BiOS (pp. 82230O-82230O). International Society for Optics and Photonics.

[9] Haustein, E., &; Schwille, P. (2004). Single-molecule spectroscopic methods.Current opinion in structural biology, 14(5), 531-540

[10] Wang, P. H. (2013). 聲學/光學解析度光聲顯微系統之開發與應用. 清華大學電機工程學系學位論文, 1-79.

[11] Song, W., Liu, W., &; Zhang, H. F. (2013). Laser-scanning Doppler photoacoustic microscopy based on temporal correlation. Applied physics letters, 102(20), 203501.

[12] Zhou, Y., Liang, J., Maslov, K. I., &; Wang, L. V. (2013). Calibration-free in vivo transverse blood flowmetry based on cross correlation of slow time profiles from photoacoustic microscopy. Optics letters, 38(19), 3882-3885.

[13] Alam, S. K., &; Parker, K. J. (1995). The butterfly search technique for estimation of blood velocity. Ultrasound in medicine &; biology, 21(5), 657-670.

[14] F. Lingvall (2004),”Time domain reconstruction methods for ultrasonic array imaging,”Ph.D. dissertion, Signal and Systems, Uppsala University, Uppsala, Sweden

[15] B. Piwakowski, and B. Delannoy(1989) ”Method for computing spatial pulse response: time domain approach,” J. Acoust. Soc. Am. 86(6), 2422-2432

[16] Saleh, Bahaa E. A. and Teich, Malvin Carl (1991). Fundamentals of Photonics Second Edition. New York: John Wiley &; Sons. ISBN 0-471-83965-5. Chapter 3, "Beam Optics," pp. 97–120.

[17] Viator, J. A., Jacques, S. L., &; Prahl, S. A. (1999). Depth profiling of absorbing soft materials using photoacoustic methods. Selected Topics in Quantum Electronics, IEEE Journal of, 5(4), 989-996.

[18] A. A. Oraevsky, S. L. Jacques, and F. K. Tittel,( 1995) “Mechanism of laser ablation for aqueous media irradiated under stress confined conditions,”J. Appl. Phys., vol. 78, pp. 1281–1289.

[19] http://omlc.ogi.edu/spectra/hemoglobin/index.html

[20] http://www.signal.uu.se/Toolbox/dream/

[21] McAleavey, S. A., &; Parker, K. J. (2001, May). Effect of decorrelation on butterfly search velocity estimator performance. In Medical Imaging 2001 (pp. 293-304). International Society for Optics and Photonics.

[22] 孫斌瀚, &; 李夢麟. (2014). 用於微細血管脈絡造影光學解析度光聲顯微影像系統之開發. 科儀新知, (198), 85-93.