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New Noise Reduction Technique for Medical Ultrasound Imaging using Gabor Filtering
Mehedi Hasan Talukder, Mitsuhara Ogiya, Masato Takanokura
Pages - 28 - 38     |    Revised - 31-03-2018     |    Published - 30-04-2018
Volume - 12   Issue - 1    |    Publication Date - April 2018  Table of Contents
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KEYWORDS
Ultrasound Images, Speckle Noise, Edge Preservation, Performance Evaluation, Gabor Filter.
ABSTRACT
Ultrasound (US) imaging is an important medical diagnostic method, as it allows the examination of several internal body organs. However, its usefulness is diminished by signal dependent noise known as speckle noise. Speckle noise degrades target detectability in ultrasound images and reduces contrast and resolution, affecting the ability to identify normal and pathological tissue. For accurate diagnosis, it is important to remove this noise from ultrasound images. In this study, a new filtering technique is proposed for removing speckle noise from medical ultrasound images. It is based on Gabor filtering. Specifically, a preprocessing step is added before applying the Gabor filter. The proposed technique is applied to various ultrasound images, and certain measurement indexes are calculated, such as signal to noise ratio, peak signal to noise ratio, structure similarity index, and root mean square error, which are used for comparison. In particular, five widely used image enhancement techniques were applied to three types of ultrasound images (kidney, abdomen and ortho). The main objective of image enhancement is to obtain a highly detailed image, and in that respect, the proposed technique proved superior to other widely used filters.
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1 R. G. Dantas, E. T. Costa. "Ultrasound Speckle Reduction Using Modified Gabor Filter". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control,Vol. 54, pp. 530-538, Mar. 2007.
2 R. N. Czerwinski, D. L. Jones, W. D. O'Brien. "Ultrasound Speckle Reduction by Directional Median Filtering". International Conference on Image Processing, IEEE, Vol. 1, pp. 358-361, Apr. 2003.
3 P. Patidar, M. Gupta, S. Srivastava, A.K. Nagawat. "Image De-noising by Various Filters for Different Noise". International Journal of Computer Applications, Vol. 9, pp. 45-50, Nov. 2010.
4 D. D. Bhattacharya, M. J. Devi, M P. Bhattacherjee. "Brain Image Segmentation Technique Using Gabor Filter Parameter". American Journal of Engineering Research, Vol. 2, pp. 127-132, Jul. 2013.
5 N. Negi, S. Mathur. "An Improved Method of Edge Detection Based on Gabor Wavelet Transform". Recent Advances in Electrical Engineering and Electronic Devices, Vol. 8, pp. 184-191, Jul. 2011.
6 M. Karaman, M. A. Kutay, G. Bozdagi. "An Adaptive Speckle Suppression Filter for Medical Ultrasonic Imaging" IEEE Transactions on Medical Imaging, vol. 14, pp. 283-292, June 1995.
7 S. Joseph, K. Balakrishnan, M.R. B. Nair, R. R. Varghese. "Ultrasound Image Despeckling using Local Binary Pattern Weighted Linear Filtering". I.J. Information Technology and Computer Science, 2013, vol. 06, pp. 1-9, June 2013.
8 Y. Guo, H. D. Cheng, J Tian, Y. Zhang. "A Novel Approach to Speckle Reduction in Ultrasound Imaging". Ultrasound in Medicine and Biology, vol. 35, pp. 628-640, Apr. 2009.
9 P. Moulin, J. Liu, "Analysis of Multiresolution Image Denoisingschemes Using Generalized Gaussian and Complexity Priors". IEEE Transaction of Information Theory, Vol. 45, pp. 909-919, Apr 1999.
10 S. Sudha, G.R. Suresh, R Sukanesh. "Speckle Noise Reduction in Ultrasound Images Using Context-based Adaptive Wavelet Thresholding". IETE Journal of Research, Vol. 55, pp. 135-143, Sep. 2014.
11 O. V. Michailovich, A. Tannenbaum. "Despeckling of Medical Ultrasound Images". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 53, pp. 64-78. Jan. 2006.
12 S. C. Kang, S. H. Hong. "A Speckle Reduction Filter Using Waveletbased Methods for Medical Imaging Application". In Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2480-2483, 2001.
13 Y. Yu, S. T. Acton. "Speckle Reducing Anisotropic Diffusion". IEEE Transactions on Image Processing, Vol. 11, pp. 1260 -1270, Nov. 2002.
14 M. H. Talukder, M. A. Islam, T. K. Ghosh, M. M. Rahman. "A New Filtering Technique for Reducing Speckle Noise From Ultrasound Images". International Journal of Research in Computer and Communication Technology, Vol. 2, pp. 685-688, Sep. 2013.
15 K. B. Eom. "Speckle Reduction in Ultrasound Images Using Nonisotropic Adaptive Filtering". Ultrasound in Medicine and Biology, Vol. 37,pp. 1677-1688, Oct. 2011.
16 R. Sivakumar, M. K. Gayathri, D. Nedumara. "Speckle Filtering of Ultrasound B-Scan Images - A Comparative Study Between Spatial And Diffusion Filter".IEEE Conference on Open System, pp. 80-85, Dec. 2010.
17 I. Njeh, O. B. Sassi, K. Chtourou, A. B. Hamid. "Speckle Noise Reduction In Breast Ultrasound Images: Smu (Srad Median Unsharp) Approch". International Multi-Conference on Systems, Signals & Devices, pp. 1-6, Mar. 2011.
18 M. M. Rahman, M. Kumar, A. Aziz, M. G. Arefin, M. S. Uddin. "Adaptive Anisotropic Diffusion Filter for Speckle Noise Reduction for Ultrasound Images". International Journal of Convergence Computing, Vol. 1, pp.50-59,Dec. 2013.
19 A. Buades, B.Coll, J. Morel "A Non-Local Algorithm for Image Denoising". In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 60-65, 2005.
20 J. Starck, E. J. Candes, D. L. Donoho. "The Curvelet Transform for Image Denoising". IEEE Transactions on image processing, Vol.11,pp.670-684 ,Jun. 2002.
21 J. Patra, H. N. Moulick, S. Mallick, A. K. Manna. "3D Wavelet SubBands Mixing for Image De-noising and Segmentation of Brain Images". American Journal of Engineering Research, Vol. 03, pp-207-221, Jul. 2014.
22 S. K. Narayanan and R. S. D. Wahidabanu, "A View on Despeckling in Ultrasound Imaging". International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 2, pp. 85-98, Sep 2009.
23 A. Islam, M. H. Talukder, M. M. Hasan, "Speckle Noise Reduction From Ultrasound Image Using Modified Binning Method and Fuzzy Inference System" International Conference on Advances in Electrical Engineering (ICAEE), pp.359-362, Dec 2013.
24 M. M. Rahman, M. H. Talukder, M. M. Rahman, "Ultrasound Image Enhancement Using Discrete Wavelet Transform based on Image Sharpening Model". American International Journal of Research in Science, Technology, Engineering & Mathematics (AIJRSTEM), Vol.15, pp. 240-244, Aug 2016.
25 R. E. Pregitha, D. V. Jegathesan, C. E. Selvakumar, "Speckle Noise Reduction in Ultrasound Fetal Images Using Edge Preserving
Mr. Mehedi Hasan Talukder
Kanagawa University - Japan
m.hasan2006@yahoo.com
Mr. Mitsuhara Ogiya
Department of Industrial Engineering and Management Faculty of Engineering, Kanagawa University Yokahama, 221-8686, Japan - Japan
Mr. Masato Takanokura
Department of Industrial Engineering and Management Faculty of Engineering, Kanagawa University Yokahama, 221-8686, Japan - Japan