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[1] H. Yu, M. Ding, and X. Zhang, “PCANet based non-local means method for speckle noise removal in ultrasound images”, PLoS One, vol. 13, no. 10, 2018. https://doi.org/10.1371/journal.pone.0205390.10.1371/journal.pone.0205390618573530312331 Search in Google Scholar

[2] J. F. Al-Asad, M. O. Butt, and A. H. Khan, “Spectral Decomposition By Schur for Medical Ultrasound Image Denoising”, IEEE - International Symposium on Advanced Electrical and Communication Technologies, 2019, https://ieeexplore.ieee.org/document/9069688.10.1109/ISAECT47714.2019.9069688 Search in Google Scholar

[3] A. Piurica, W. Philips, I. Lemahieu, and M. Acheroy, “A versatile wavelet domain noise filtration technique for medical imaging”, IEEE Trans. Med. Imaging, vol. 22, no. 3, pp. 323331, 2003, https://doi.org/10.1109/tmi.2003.809588.10.1109/TMI.2003.80958812760550 Search in Google Scholar

[4] F. Baselice, “Ultrasound Image Despeckling Based on Statistical Similarity”, Ultrasound in Medicine &. Biology., vol. 43, no. 9, pp. 20652078, 2017, https://doi.org/10.1016/j.ultrasmedbio.2017.05.006.10.1016/j.ultrasmedbio.2017.05.00628651920 Search in Google Scholar

[5] V. S. Frost, J. A. Stiles, K. S. Shanmugan, and J. C. Holtzman, “A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise”, IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-4, no. 2, pp. 157-166, 1982. https://doi.org/10.1109/tpami.1982.4767223.10.1109/TPAMI.1982.476722321869022 Search in Google Scholar

[6] D. T. Kuan, A. A. Sawchuk, T. C. Strand, and P. Chavel, “Adaptive Noise Smoothing Filter For Images With Signal-Dependent Noise”, IEEE Trans. Pattern Anal. Mach. Intell., vol. PAMI-7, no. 2, pp. 165-177, 1985, https://doi.org/10.1109/tpami.1985.4767641.10.1109/TPAMI.1985.4767641 Search in Google Scholar

[7] J.-S. Lee, “Digital Image Enhancement and Noise Filtering by Use of Local Statistics”, IEEE Trans. Pattern Anal. Mach. Intell. , vol. PAMI-2, no. 2, pp. 165-168, 1980, https://doi.org/10.1109/tpami.1980.4766994.10.1109/TPAMI.1980.476699421868887 Search in Google Scholar

[8] Yu Yongjian and S. T. Acton, “Speckle reducing anisotropic diffusion”, IEEE Trans. Image Process., vol. 11, no. 11, pp. 1260-12 70, (2002). https://doi.org/10.1109/tip.2002.804276.10.1109/TIP.2002.80427618249696 Search in Google Scholar

[9] C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images”, Proceedings of the 1998 IEEE International Conference on Computer Vision, pp. 839-846, 1998, https://users.soe.ucsc.edu/manduchi/Papers/ICCV98.pdf. Search in Google Scholar

[10] A. Vishwa and S. Sharma, “Modified Method for Denoising the Ultrasound Images by Wavelet Thresholding”, Intell. Syst. Appl., vol. 4, no. 6, pp. 25-30, 2012, https://doi.org/10.5815/ijisa.2012.06.03.10.5815/ijisa.2012.06.03 Search in Google Scholar

[11] Y. Farouj, J.-M. Freyermuth, L. Navarro, M. Clausel, and P. Delachartre, “Hyperbolic Wavelet-Fisz Denoising for a Model Arising in Ultrasound Imaging”, IEEE Trans. Comput. Imaging, vol. 3, no. 1, pp. 1-10, 2017, https://doi.org/10.1109/tci.2016.2625740.10.1109/TCI.2016.2625740 Search in Google Scholar

[12] F. Zaki, Y. Wang, H. Su, X. Yuan, and X. Liu, “Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography”, Biomed. Opt. Express, vol. 8, no. 5, p. 2720, 2017, https:https://doi.org/10.2478/jee-2021-0032.org/10.1364/boe.8.002720. Search in Google Scholar

[13] Y. Zhan, M. Ding, L. Wu, and X. Zhang, “Non-local means method using weight refining for despeckling of ultrasound images”, Signal Processing, vol. 103, pp. 201-213, 2014. https://doi.org/10.1016/j.sigpro.2013.12.019.10.1016/j.sigpro.2013.12.019 Search in Google Scholar

[14] L. Zhu, C.-W. Fu, M. S. Brown, and P.-A. Heng, “A Non-Local Low-Rank Framework for Ultrasound Speckle Reduction”, The IEEE Conference on Computer Vision and Pattern Recognition (, CVPR ), pp. 5650-5658, 2017, https://ieeexplore.ieee.org/document/8099543. Search in Google Scholar

[15] J. Yang, J. Fan, D. Ai, X. Wang, Y. Zheng, S. Tang, and Y. Wang, “Local statistics and non-local mean filter for speckle noise reduction in medical ultrasound image”, Neurocomputing, vol. 195, pp. 88-95, 2016, https://doi.org/10.1016/j.neucom.2015.05.140.10.1016/j.neucom.2015.05.140 Search in Google Scholar

[16] C. A. N. Santos, D. L. N. Martins, and N. D. A. Mascarenhas, “Ultrasound Image Despeckling Using Stochastic Distance-Based BM3D”, IEEE Trans. Image Process., vol. 26, no. 6, pp. 2632-2643, 2017, https://doi.org/10.1109/tip.2017.2685339.10.1109/TIP.2017.268533928333627 Search in Google Scholar

[17] Y.Wu, B. Tracey, P. Natarajan, and J. P. Noonan, “Probabilistic non-local means”, IEEE Signal Process. Lett., vol. 20, no. 8, pp. 763-766, 2013. https://doi.org/10.1109/lsp.2013.2263135.10.1109/LSP.2013.2263135 Search in Google Scholar

[18] J. F. Al-Asad and A. H. Khan, “QR based de-noising scheme for medical ultrasound images”, 9 th IEEE-GCC Conference and Exhibition, GCCCE,. Search in Google Scholar

[19] A. H. Khan, J. F. Al-Asad, and G. Latif, “Speckle suppression in medical ultrasound images through Schur decomposition”, IET Image Process., vol. 12, no. 3, pp. 307-313, 2018, https://doi.org/10.1049/iet-ipr.2017.0411.10.1049/iet-ipr.2017.0411 Search in Google Scholar

[20] M. O. Butt, J. F. Al-Asad, A. H. Khan, and D. N. F. Awang Iskandar, “Ultrasound image denoising using orthogonal decomposition in frequency domain”, IEEE 9 th International Conference on System Engineering and Technology, ICSET 2019 - Proceeding, pp. 349-353. 2019, https://ieeexplore.ieee.org/document/8906441.10.1109/ICSEngT.2019.8906441 Search in Google Scholar

[21] Y. Chen, M. Zhang, H.-M. Yan, Y.-J. Li, and K.-F. Yang, “A New Ultrasound Speckle Reduction Algorithm Based on Super- pixel Segmentation and Detail Compensation”, Appl. Sci., vol. 9, no. 8, p. 1693, 2019, https://doi.org/10.3390/app9081693.10.3390/app9081693 Search in Google Scholar

[22] Z. Hosseini and M. H. Bibalan, “Speckle noise reduction of ultra- sound images based on neighbor pixels averaging”, 25 th Iranian Conference on Biomedical Engineering and 3 rd International Iranian Conference on Biomedical Engineering, ICBME 2018, https://ieeexplore.ieee.org/document/8703576.10.1109/ICBME.2018.8703576 Search in Google Scholar

[23] O. V. Michailovich and A. Tannenbaum, “Despeckling of medical ultrasound images”, IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 53, no. 1, pp. 64-78, 2006, https://ieeex-plore.ieee.org/stamp/stamp.jsp?arnumber=1588392.10.1109/TUFFC.2006.1588392 Search in Google Scholar

[24] J. A. Jensen, “Field: A Program for Simulating Ultrasound Systems”, Paper presented at the 10 th Nordic-Baltic Conference on Biomedical Imaging. Medical & Biological Engineering & Computing, Supplement 1, Part 1, vol. 34, pp. 351-353, 1996. https://field-ii.dk/documents/jajnbc1996.pdf. Search in Google Scholar

[25] A. Khvostikov, A. Krylov, J. Kamalov, and A. Megroyan, “Ultrasound despeckling by anisotropic diffusion and total variation methods for liver fibrosis diagnostics”, Signal Processing: Image Communication, vol. 59 pp. 3-11, 2017, https://doi.org/10.1016/j.image.2017.09.005.10.1016/j.image.2017.09.005 Search in Google Scholar

[26] J. Antony, “A Gallery of High-Resolution, Ultrasound, Color Doppler & 3D Images”, Ultrasound Image Gallery, 2019, https://www.ultrasound-images.com. Search in Google Scholar

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