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Despeckling of Ultrasound Images Using Modified Local Statistics Mean Variance Filter

Ranu Gupta1,3,*, Rahul Pachauri2,3, Ashutosh Singh1,4

Department of Electronics and Communication
Department of Computer Science
Jaypee University of Engineering and Technology, Raghogarh, Guna (M.P.) 473226 , India.
Thapar Institute of Engineering and Technology University, Patiala, 147004, India .

*Corresponding author: Ranu Gupta. Email: email; email.

Computer Modeling in Engineering & Sciences 2018, 114(1), 19-32. https://doi.org/10.3970/cmes.2018.114.019

Abstract

This article presents an improved method of despeckling the ultrasound medical images. In this paper a modified local statistics mean variance filter method has been proposed. In the proposed method, more consideration is given to local statistics since local statistical features are more important rather than global features.Various parameters like mean square error, peak signal to noise ratio, quality index, and structural similarity index measure are calculated to analyze the quality of the despeckled image.

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Cite This Article

APA Style
Gupta, R., Pachauri, R., Singh, A. (2018). Despeckling of ultrasound images using modified local statistics mean variance filter. Computer Modeling in Engineering & Sciences, 114(1), 19-32. https://doi.org/10.3970/cmes.2018.114.019
Vancouver Style
Gupta R, Pachauri R, Singh A. Despeckling of ultrasound images using modified local statistics mean variance filter. Comput Model Eng Sci. 2018;114(1):19-32 https://doi.org/10.3970/cmes.2018.114.019
IEEE Style
R. Gupta, R. Pachauri, and A. Singh, “Despeckling of Ultrasound Images Using Modified Local Statistics Mean Variance Filter,” Comput. Model. Eng. Sci., vol. 114, no. 1, pp. 19-32, 2018. https://doi.org/10.3970/cmes.2018.114.019



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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