在過去使用光聲顯微技術的研究中，軸向分量的血流速度估計方法大部分都是使用互相關技術或是一維自相關技術。此外，過去的相關研究大多都使用不同的技術去分別估計軸向分量及橫向分量的速度，這也使得必須使用更多的運算時間才能估計出血流的絕對速度。
本研究中，我們提出一個在光學解析度光聲顯微術下適用的嶄新的血流速度估計方法，使用二維自相關技術同時估計軸向及橫向分量的速度。軸向分量速度方面，我們提出的方法不僅可以估計都普勒頻率，還能同時估計光聲訊號的中心頻率，且計算複雜度相較於傳統的一維自相關技術是相差不大的。橫向分量速度方面，我們可以透過估計光聲訊號都普勒頻率的頻寬來計算橫向分量的速度。簡而言之，我們提出的方法可以同時且更精確地估計軸向及橫向分量的速度。
根據模擬結果，我們提出的血流估計技術與傳統一維技術相比，在訊雜比在25dB與15dB的情況下，軸向分量速度估計的標準差可以分別減少63%與80.5%，而橫向分量速度估計的標準可以分別減少82%與83.3%。根據實驗結果，我們提出的血流估計技術相較一維估計技術，在訊雜比在25dB的情況下，軸向分量速度估計的標準差可以減少33.1%，橫向分量速度估計的標準可以減少27.1%。上述的結果說明了，在相同程度的訊雜比之下，我們提出的血流速度估計技術相較過去的方法能夠有效提升血流估計的準確度。

In previous studies, for photoacoustic microscopy, axial flow estimation algorithms are mainly based on cross-correlation and 1-D autocorrelation techniques. In addition, previous studies adopt different techniques to estimate the axial and lateral flow respectively, which may take much time to estimate the entire flow. In this study, we propose a novel 2-D autocorrelation based blood flow estimation algorithm which estimates both axial and lateral flow at the same time for optical resolution photoacoustic microscopy (OR-PAM). For axial flow, our proposed method not only considers Doppler frequency shift as the 1-D autocorrelation technique does, but also estimates the photoacoustic center frequency of the acquired OR-PAM signal, which is assumed to be the same as that of the used ultrasound transducer in the 1-D autocorrelation technique and in practice is not, while the computational complexity remains almost the same as that of the 1-D autocorrelation method. For lateral flow, the proposed method can also estimate the Doppler frequency bandwidth which is proportional to lateral speed and thus is used for lateral speed estimation. In a word, the proposed method can estimate both axial and lateral flow more precisely and simultaneously. Simulation results showed that while the SNR is 25 dB and 15 dB respectively, the proposed 2-D axial flow estimator can efficiently reduce the standard deviation of velocity estimation from conventional axial methods by 63 percent and 80.5 percent, and the used 2-D lateral flow estimator can efficiently reduce the standard deviation of velocity estimation from 1-D lateral methods by 82 percent and 83.3 percent. Experimental results showed that while the SNR is 25 dB, the proposed 2-D axial flow estimator can efficiently reduce the standard deviation of velocity estimation from conventional axial methods by 33.1 percent, and the used 2-D lateral flow estimator can efficiently reduce the standard deviation of velocity estimation from 1-D lateral methods by 27.1 percent. The above results demonstrate a more precise flow estimation than that provided by the methods in previous studies under the same signal-to-noise ratio.

摘要…………………………………………………………I
Abstract…………………………………………………………III
Table of Contents…………………………………………………………V
List of Figures…………………………………………………………VII
Chapter 1 Introduction…………………………………………………………1
1.1 Blood Flow Estimation with OR-PAM…………………………………………………………1
1.2 Conventional Methods…………………………………………………………1
1.2.1 Axial Flow…………………………………………………………1
1.2.2 Lateral Flow…………………………………………………………3
1.3 Motivations…………………………………………………………3
1.4 Composition of the Thesis…………………………………………………………4
Chapter 2 Materials and Methods…………………………………………………………5
2.1 Doppler Dataset…………………………………………………………5
2.2 Proposed Methods…………………………………………………………6
2.2.1 Axial Flow…………………………………………………………6
2.2.2 Lateral Flow…………………………………………………………9
2.3 Theoretical Maximum and Minimun Achievable Speed……………11
2.4 Simulation Parameters…………………………………………………………12
2.5 Experimental Setup…………………………………………………………13
Chapter 3 Results and Discussion…………………………………………………………16
3.1 Size of Region of Interest…………………………………………………………16
3.2 Simulation Results…………………………………………………………22
3.2.1 Single Absorber…………………………………………………………22
3.2.2 Multiple Absorbers…………………………………………………………26
3.3 Maximum and Minimun Achievable Speed…………………………………………………………30
3.4 Experimetal Results…………………………………………………………33
Chapter 4 Conclusions and Future Work…………………………………………………………41
4.1 Conclusions…………………………………………………………41
4.2 Future Work…………………………………………………………42
References…………………………………………………………42

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