International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 15, No. 3, 8 Jun. 2023
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Design and Implementation of Speckle Noise Reduction Algorithm Using 2D Ultrasound Image
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Author(s)
Index Terms
Ultrasound Images, Speckle Noise, Image Processing, Noise Reduction, SSIM, SNR, RMSE
Abstract
Ultrasound is mostly used for diagnosis to deal with the specific abnormality in human body. To observe the internal organs including liver, kidneys, pancreas, thyroid gland, ovaries etc. ultrasound can be used. In diagnostic applications, 2 to 18 MHz frequencies are used. The sound wave explorations occurred through soft tissue and fluids. It bounces back as echoes from denser surfaces and creates an image. While producing ultrasound images from echo signal speckle noise is induced in a multiplicative way. Thus, speckle becomes the key challenge for ultrasound imaging. Several speckle reducing linear, non-linear and anisotropic diffusion-based methods are implemented to preserve the sharp edges of ultrasound images. Those methods contain lake of smoothing and edge preservation. However, this research proposed a combined method of adaptive filter (wiener) and anisotropic diffusion (modified Perona Malik) for speckle reduction of 2D ultrasound images by retain the important anatomical features. A comparison of all the existing methods studied based on the simulated experiment. To test the methods liver, kidney, heart and pancreas noise free images are used. Then, speckle noise is manually added with distinguished variance in between 0.02 and 0.20. Quality metrics are used to test the performance and show the improvements of the proposed method. About 71.79% structure similarity (SSIM), 66.72% root mean square error (RMSE), 56.93% signal to noise ratio (SNR), and 62.30% computational time are improved on average compared with the other methods.
Cite This Paper
Md. Habibur Rahman, Md. Selim Hossain, Farhana Islam, "Design and Implementation of Speckle Noise Reduction Algorithm Using 2D Ultrasound Image", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.15, No.3, pp. 31-47, 2023. DOI:10.5815/ijigsp.2023.03.03
Reference
[1]Goel Navnish, Akhilendra Yadav, and Brij Mohan Singh. “Medical image processing: A review.” in Second International Innovative Applications of Computational Intelligence on Power, Energy and Controls with their Impact on Humanity (CIPECH). IEEE, 2016.
[2]Uddin, Muhammad Shahin, et al. “Intelligent estimation of noise and blur variances using ANN for the restoration of ultrasound images.” Applied optics 55.31 (2016): 8905-8915.
[3]Uddin, Muhammad Shahin, et al. “Speckle-reduction algorithm for ultrasound images in complex wavelet domain using genetic algorithm-based mixture model.” Applied optics 55.15 (2016): 4024-4035.
[4]Martınez, Carlos López. “Multidimensional speckle noise, modelling and filtering related to SAR data.” Unpublished Ph. D. dissertation, Universitat Politecnica De Catalunya, Barcelona, Spain (2003).
[5]Yu Y, Acton ST. “Speckle reducing anisotropic diffusion.” IEEE Transactions on image processing. 2002 Nov; 11(11):1260-70.
[6]Uddin MS, Tahtali M, Lambert AJ, Pickering MR. “Speckle reduction for ultrasound images using nonlinear multi-scale complex wavelet diffusion.” in IEEE International Conference on Signal and Image Processing Applications 2013 Oct 8 (pp. 31-36). IEEE.
[7]Carovac, Aladin, Fahrudin Smajlovic, and Dzelaludin Junuzovic. “Application of ultrasound in medicine.” Acta Informatica Medica 19.3 (2011): 168.
[8]Bioucas-Dias, José M., and Mário AT Figueiredo. “Multiplicative noise removal using variable splitting and constrained optimization.” IEEE Transactions on Image Processing 19, no. 7 (2010): 1720-1730.
[9]Zaidman, Craig M.; van Alfen, Nens (2016-04-01). “Ultrasound in the Assessment of Myopathic Disorders". Journal of Clinical Neurophysiology. 33 (2): 103 111
[10]Y. Yue and et al., Nonlinear Multiscale Wavelet Diffusion for Speckle Suppression and Edge Enhancement in Ultrasound Images. IEEE Transactions on Medical Imaging. vol. 25, no. 3, pp. 297–311, (2006).
[11]Bini, A. and Bhat, M., “De speckling low SNR, low contrast ultrasound images via anisotropic level set diffusion,” Multidimensional Systems and Signal Processing, 1–25 (2012).
[12]D. Adam, S. Beilin-Nissan, Z. Friedman, and V. Behar, “The combined effect of spatial compounding and nonlinear filtering on the speckle reduction in ultrasound images,” Ultrasonics 44, 166–181 (2006).
[13]S. Mallat. “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation.” IEEE Transactions on Pattern Analysis and Machine Intelligence. vol. 11, no. 7, pp. 674–693, (1989).
[14]A. Milkowski, Y. Li, D. Becker, and S. O. Ishrak, “Speckle reduction imaging, Technical White Paper-General Electric Health Care (Ultrasound)” Last accessed on July, Vol. 9 (2009).
[15]K. Z. Abd-Elmoniem, A.-B. M. Youssef, and Y. M. Kadah, “Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion,” IEEE Trans. Biomed. Eng. 49, 997–1014 (2002)
[16]M. C. Motwani, M. C. Gadiya, R. C. Motwani, and F. C. Harris, “Survey of image denoising techniques,” in Proceedings of GSPX (2004)
[17]Karaoğlu, O., Bilge, H. Ş., & Uluer, İ. (2022). Removal of speckle noises from ultrasound images using five different deep learning networks. Engineering Science and Technology, an International Journal, 29, 101030.
[18]Abrahim, B. A., & Kadah, Y. (2011, February). Speckle noise reduction method combining total variation and wavelet shrinkage for clinical ultrasound imaging. In 2011 1st Middle East Conference on Biomedical Engineering (pp. 80-83). IEEE.
[19]Gupta, Kanika, and S. K. Gupta. “Image denoising techniques-a review paper.” International Journal of Innovative Technology and Exploring Engineering (IJITEE) Vol. 2(4) (2013): 6-9.
[20]S. Sudha, G. R. Suresh, and R. Sukanesh. “Speckle noise reduction in ultrasound images by wavelet thresholding based on weighted variance.” International Journal of Computer Theory and Engineering, pp. 1793– 8201, (2009).
[21]Sudha, S., Suresh, G.R. and Sukanesh, R., 2009. “Speckle noise reduction in ultrasound images using context-based adaptive wavelet thresholding.” IETE Journal of Research, 55(3), pp.135-143.
[22]Makovoz, D. (2006, August). “Noise variance estimation in signal processing.” in IEEE International Symposium on Signal Processing and Information Technology (pp. 364-369). IEEE.
[23]Wang, Zhou; Bovik, A.C.; Sheikh, H.R.; Simoncelli, E.P. (2004-04-01). “Image quality assessment: from error visibility to structural similarity.” IEEE Transactions on Image Processing. 13 (4): 600–612.
[24]Renieblas, G. P., Nogués, A. T., González, A. M., León, N. G., & Del Castillo, E. G. (2017). “Structural similarity index family for image quality assessment in radiological images.” Journal of Medical Imaging, 4(3), 035501.
[25]Finn, S., Glavin, M., & Jones, E. (2011). “Echocardiographic speckle reduction comparison.” IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 58(1), 82-101.
[26]Finn, S., Jones, E. and Glavin, M., 2009, September. “Objective and subjective evaluations of quality for speckle reduced echocardiography.” in International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 503-506). IEEE.
[27]Gupta, N., Swamy, M.N.S. and Plotkin, E., 2005. “Despeckling of medical ultrasound images using data and rate adaptive lossy compression.” IEEE Transactions on Medical Imaging, 24(6), pp.743-754.
[28]Rt. Duplex Kidney, available: https://www.ultrasound-images.com/kidneys/, accessed date: 10-03-2022
[29]SAMSUNG MEDISON, Liver, available: https://www.medison.ru/ultrasound/gal763.htm, accessed date: 17-04-2022
[30]Fatty Liver, B-mode, available: https://zenodo.org/record/1009146#.XMhhvIkzbIV, accessed date: 01-12-2021
[31]Liver metastases, available: https://www.ultrasound-images.com/liver/, accessed date: 20-02-2022
[32]SAMSUNG MEDISON, Pancreas, THI mode, available: https://www.medison.ru/ultrasound/gal635.htm, accessed date: 02-05-2022
[33]SAMSUNG MEDISON, Heart, Fetus, available: https://www.medison.ru/ultrasound/gal758.htm, accessed date: 10-01-2022