高能聚焦超音波 (High-intensity focused ultrasound, HIFU) 的超音波監測成像具有低成本、非侵入性和即時成像等優點。然而，在超音波成像系統運行的過程中，HIFU的發射信號通常會產生嚴重的聲學干擾，這是因為HIFU的發射信號強度遠高於成像的信號強度。在過去的研究中，有提出像是雙極序列Golay編碼技術，該技術利用成本較低的超音波脈衝發射器發送傳輸訊號，以達到高訊號雜訊比的HIFU治療的監測成像，並將接收到的資料進行解碼，來還原影像的解析度，同時消除HIFU干擾。然而，Golay編碼的解碼需要仰賴兩次發射序列之間的互補性，因此容易產生運動假影 (Motion artifact)。在本研究中，我們提出了一種新型的單次發射雙極序列最小旁瓣峰值 (Minimum-Peak-Sidelobe, MPS) 編碼來同時消除HIFU干擾和避免運動假影產生。MPS發射序列的設計上要求正負位元的數目剛好相等且位元時長會是HIFU波形週期的整數倍，另外還需進行不同編碼的排列組合搜索以獲取最佳編碼序列，對應的回聲信號會先通過匹配濾波器進行第一階段解碼以消除HIFU干擾並提高影像的訊號雜訊比，之後再使用維納濾波器進行第二階段的脈衝壓縮以提升影像品質。我們分別進行了模擬和實驗比較脈衝反相相減 (Pulse-inversion subtraction, PIS)、Golay解碼和MPS解碼在超音波監測影像的性能。結果顯示MPS解碼可在組織運動的情況下成功消除HIFU干擾並維持成像品質。相比之下，uncode PIS和Golay解碼則會被未消除HIFU成分影響到最終的HIFU監控效果，綜上所述，單次發射的MPS編碼序列能夠在臨床上實現即時調整HIFU聚焦位置的治療應用。此外，儘管透過點阻濾波器也可以做到單次發射的HIFU干擾消除，但該技術的缺點是需要在HIFU干擾消除和斑點劣化之間進行權衡。

High-intensity focused ultrasound (HIFU) monitoring imaging using ultrasound (US) offers advantages such as low cost, non-invasiveness, and real-time imaging. However, during the operation of the US imaging system, the transmission signals of HIFU often generate significant acoustic interfer-ence due to their much higher intensity compared to the imaging signals. In previous studies, bipolar sequences such as Golay can be readily transmitted by US pulser hardware with the full driving voltage for high signal-to-noise ratio (SNR) monitoring of HIFU treatment. The subsequent decoding restores the image resolution of US monitoring and also removes acoustic interference from simultaneous HIFU transmission. However, Golay suffers from poten-tial motion artifacts since its decoding demands two complementary se-quences. In this study, we suggest a novel single-transmit bipolar sequence with minimum-peak-sidelobe (MPS) level to eliminate HIFU interference and avoid motion artifacts. The MPS code is designed with an equal number of positive and negative bits and the bit duration should be an integer multiple of the period of the HIFU waveform. In addition, we will search for different permutations in order to obtain the optimal encoding. The received imaging echo is firstly decoded by matched filtering to cancel HIFU interference and enhance image SNR. Then, Wiener filtering is applied as the second-stage pulse compression to improve the image quality of US monitoring. Simula-tions and experiments are performed to compare among uncode transmissions with pulse-inversion subtraction (PIS), Golay decoding, and MPS decoding for their performance in US monitoring images. The results show that MPS decoding successfully removes HIFU interference even in the presence of tissue motion. The image quality of uncode PIS and Golay decoding, on the other hand, is compromised by the uncancelled HIFU components which degrade their image quality. In summary, the MPS encoding sequence with a single-transmit enables real-time adjustment of HIFU focal position for clinical therapeutic applications. Though notch filtering also allows HIFU elimination using single-transmit waves, it suffers from the tradeoff between residual HIFU and speckle deterioration.

[1] 沈哲州，「醫用超音波影像上課講義」，國立臺灣科技大學電機所，民國110年。
[2] Y. Wang, Z. B. Wang, and Y. H. Xu, “Efficacy, Efficiency, and Safety of Magnetic Resonance-Guided High-Intensity Focused Ultrasound for Ablation of Uterine Fibroids: Comparison with Ultrasound-Guided Method,” Korean J. Radiol., vol. 19, no. 4, pp. 724-732, 2018.
[3] H. Azzouz, and J. J. M. C. H. de la Rosette, “HIFU: Local Treatment of Prostate Cancer,” EAU-EBU Updat. Ser., vol. 4, no. 2, pp. 62-70, 2006.
[4] S. Vaezy, R. Martin, and L. Crum, “High intensity focused ultrasound: a method of hemostasis,” Echocardiography, vol. 18, no. 4, pp. 309-315, 2001.
[5] E. E. Konofagou, Y. S. Tung, J. Choi et al., “Ultrasound-induced blood-brain barrier opening,” Curr. Pharm. Biotechnol., vol. 13, no. 7, pp. 1332-1345, 2012.
[6] I. Rivens, A. Shaw, J. Civale et al., “Treatment monitoring and thermometry for therapeutic focused ultrasound,” Int. J. Hyperthermia, vol. 23, no. 2, pp. 121-139, 2007.
[7] K. Kuroda, “MR techniques for guiding high-intensity focused ultrasound (HIFU) treatments,” J. Magn. Reson. Imag., vol. 47, no. 2, pp. 316-331, 2018.
[8] M. A. Solovchuk, S. C. Hwang, H. Chang et al., “Temperature elevation by HIFU in ex vivo porcine muscle: MRI measurement and simulation study,” Med. Phys., vol. 41, no. 5, art. no. 052903, 2014.
[9] S. Vaezy, X. Shi, R. W. Martin et al., “Real-time visualization of high-intensity focused ultrasound treatment using ultrasound imaging,” Ultrasound Med. Biol., vol. 27, no. 1, pp. 33-42, 2001.
[10] D. Liu, and E. S. Ebbini, “Real-time 2-D temperature imaging using ultrasound,” IEEE Trans. Biomed. Eng., vol. 57, no. 1, pp. 12-16, 2010.
[11] R. M. Arthur, J. W. Trobaugh, W. L. Straube et al., “Temperature dependence of ultrasonic backscattered energy in motion-compensated images,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 52, no. 10, pp. 1644-1652, 2005.
[12] P. D. Bevan, and M. D. Sherar, “B-scan ultrasound imaging of thermal coagulation in bovine liver: frequency shift attenuation mapping,” Ultrasound Med. Biol., vol. 27, no. 6, pp. 809-817, 2001.
[13] M. A. Abbass, J. K. Killin, N. Mahalingam et al., “Real-Time Spatiotemporal Control of High-Intensity Focused Ultrasound Thermal Ablation Using Echo Decorrelation Imaging in ex Vivo Bovine Liver,” Ultrasound Med. Biol., vol. 44, no. 1, pp. 199-213, 2018.
[14] M. A. Abbass, A. J. Garbo, N. Mahalingam et al., “Optimized Echo Decorrelation Imaging Feedback for Bulk Ultrasound Ablation Control,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 65, no. 10, pp. 1743-1755, 2018.
[15] N. R. Owen, M. R. Bailey, J. Hossack et al., “A method to synchronize high-intensity, focused ultrasound with an arbitrary ultrasound imager,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 53, no. 3, pp. 645-650, 2006.
[16] S. Pichardo, A. Gelet, L. Curiel et al., “New integrated imaging high intensity focused ultrasound probe for transrectal prostate cancer treatment,” Ultrasound Med. Biol., vol. 34, no. 7, pp. 1105-1116, 2008.
[17] J. S. Jeong, J. H. Chang, and K. K. Shung, “Ultrasound transducer and system for real-time simultaneous therapy and diagnosis for noninvasive surgery of prostate tissue,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 56, no. 9, pp. 1913-1922, 2009.
[18] J. S. Jeong, J. M. Cannata, and K. K. Shung, “Adaptive HIFU noise cancellation for simultaneous therapy and imaging using an integrated HIFU/imaging transducer,” Phys. Med. Biol., vol. 55, no. 7, pp. 1889-1902, 2010.
[19] J. H. Song, Y. Yoo, T. K. Song et al., “Real-time monitoring of HIFU treatment using pulse inversion,” Phys. Med. Biol., vol. 58, no. 15, pp. 5333-5350, 2013.
[20] E.-J. Shin, B. Kang, and J. Chang, “Real-Time HIFU Treatment Monitoring Using Pulse Inversion Ultrasonic Imaging,” Appl. Sci., vol. 8, no. 11, art. no. 2219, 2018.
[21] C. C. Shen, R. C. Lin, and N. H. Wu, “Golay-Encoded Ultrasound Monitoring of Simultaneous High-Intensity Focused Ultrasound Treatment: A Phantom Study,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 69, no. 4, pp. 1370-1381, 2022.
[22] M. N. Cohen, M. R. Fox, and J. M. Baden, “Minimum peak sidelobe pulse compression codes,” in Proc. IEEE Int. Radar Conf., 1990, pp. 633-638.
[23] C. J. Nunn, and G. E. Coxson, “Best-known autocorrelation peak sidelobe levels for binary codes of length 71 to 105,” IEEE Transactions on Aerospace and Electronic Systems, vol. 44, no. 1, pp. 392-395, 2008.
[24] C. H. Hu, R. Liu, Q. Zhou et al., “Coded excitation using biphase-coded pulse with mismatched filters for high-frequency ultrasound imaging,” Ultrasonics, vol. 44, no. 3, pp. 330-336, 2006.
[25] S. A. Jadwaa, “Wiener Filter based Medical Image De-noising,” International Journal of Science and Engineering Applications, vol. 7, pp. 318-323, 2018.
[26] J. A. Jensen, “Field: A Program for Simulating Ultrasound Systems,” Med. Biol. Eng. Comput., vol. 34, pp. 351-353, 1996.
[27] J. A. Jensen, and N. B. Svendsen, “Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 39, no. 2, pp. 262-267, 1992.
[28] P. C. Li, C. J. Cheng, and C. K. Yeh, “On velocity estimation using speckle decorrelation,” IEEE Trans. Ultrason., Ferroelect., Freq. Control, vol. 48, no. 4, pp. 1084-1091, 2001.
[29] J. Seo, N. Koizumi, M. Mitsuishi et al., “Ultrasound image based visual servoing for moving target ablation by high intensity focused ultrasound,” Int. J. Med. Robot. Comput. Assist. Surg., vol. 13, no. 4, e1793, 2017.