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Current Chinese Computer Science

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ISSN (Print): 2665-9972
ISSN (Online): 2665-9964

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Editorial

Noise Removal Issues in Ultrasound Images

Author(s): Ayush Dogra,* and Bhawna Goyal

Volume 2, Issue 1, 2022

Published on: 28 June, 2022

Article ID: e300322202820 Pages: 3

DOI: 10.2174/2665997202666220330101445

[1]
M. Jabarulla, and H.N. Lee, "Speckle reduction on ultrasound liver images based on a sparse representation over a learned dictionary", Appl. Sci., vol. 8, no. 6, p. 903, 2018.
[http://dx.doi.org/10.3390/app8060903]
[2]
Ognjen Magud, Eva Tuba, and N. Bacanin, "Medical ultrasound image speckle noise reduction by adaptive median filter", Wseas Trans. Biol. Biomed., vol. 14, pp. 38-46, 2017.
[3]
M. Mafi, S. Tabarestani, M. Cabrerizo, A. Barreto, and M. Adjouadi, "Denoising of ultrasound images affected by combined speckle and Gaussian noise", IET Image Process., vol. 12, no. 12, pp. 2346-2351, 2018.
[http://dx.doi.org/10.1049/iet-ipr.2018.5292]
[4]
S. Sudharson, T. Pratap, and P. Kokil, "Noise level estimation for effective blind despeckling of medical ultrasound images", Biomed. Signal Process. Control, vol. 68, p. 102744, 2021.
[http://dx.doi.org/10.1016/j.bspc.2021.102744]
[5]
P. Afshari, C. Zakian, and V. Ntziachristos, "Improving ultrasound images with elevational angular compounding based on acoustic refraction", Sci. Rep., vol. 10, no. 1, p. 18173, 2020.
[http://dx.doi.org/10.1038/s41598-020-75092-8] [PMID: 33097780]
[6]
J. Zhang, X. Xiu, J. Zhou, K. Zhao, Z. Tian, and Y. Cheng, "A novel despeckling method for medical ultrasound images based on the nonsubsampled shearlet and guided filter", Circuits Syst. Signal Process., vol. 39, no. 3, pp. 1449-1470, 2020.
[http://dx.doi.org/10.1007/s00034-019-01201-2]
[7]
D.M. Alex, and D.A. Chandy, Evaluation of inpainting in speckled and despeckled 2D ultrasound medical images.In: 2020 Advanced Computing and Communication Technologies for High Performance Applications., ACCTHPA, 2020, pp. 221-225.
[http://dx.doi.org/10.1109/ACCTHPA49271.2020.9213203]
[8]
S.K. Jain, and R.K. Ray, "Non-linear diffusion models for despeckling of images: Achievements and future challenges", IETE Tech. Rev., vol. 37, no. 1, pp. 66-82, 2020.
[http://dx.doi.org/10.1080/02564602.2019.1565960]
[9]
P.T. Akkasaligar, and S. Biradar, "Automatic segmentation and analysis of renal calculi in medical ultrasound images", Pattern Recognit. Image Anal., vol. 30, no. 4, pp. 748-756, 2020.
[http://dx.doi.org/10.1134/S1054661820040021]
[10]
H. Aghababaei, and G. Ferraioli, "Statistical indices for despeckling evaluation in multichannel SAR images", IEEE Geosci. Remote Sens. Lett., vol. 18, no. 2, pp. 316-320, 2020.
[http://dx.doi.org/10.1109/LGRS.2020.2973462]
[11]
L. Basavarajappa, J. Baek, S. Reddy, J. Song, H. Tai, G. Rijal, K.J. Parker, and K. Hoyt, "Multiparametric ultrasound imaging for the assessment of normal versus steatotic livers", Sci. Rep., vol. 11, no. 1, p. 2655, 2021.
[http://dx.doi.org/10.1038/s41598-021-82153-z] [PMID: 33514796]
[12]
P. Kokil, and S. Sudharson, "Despeckling of clinical ultrasound images using deep residual learning", Comput. Methods Programs Biomed., vol. 194, p. 105477, 2020.
[http://dx.doi.org/10.1016/j.cmpb.2020.105477] [PMID: 32454323]
[13]
H. Li, J. Weng, Y. Shi, W. Gu, Y. Mao, Y. Wang, W. Liu, and J. Zhang, "An improved deep learning approach for detection of thyroid papillary cancer in ultrasound images", Sci. Rep., vol. 8, no. 1, p. 6600, 2018.
[http://dx.doi.org/10.1038/s41598-018-25005-7] [PMID: 29700427]
[14]
S. Wu, Q. Zhu, and Y. Xie, Evaluation of various speckle reduction filters on medical ultrasound images. 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013, pp. 1148-1151.

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