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Current Medical Imaging

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ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

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Research Article

Speckle Noise Diffusion in Knee Articular Cartilage Ultrasound Images

Author(s): Muhammad Ali Shoaib, Md Belayet Hossain, Yan Chai Hum, Joon Huang Chuah, Maheza Irna Mohd Salim and Khin Wee Lai *

Volume 16, Issue 6, 2020

Page: [739 - 751] Pages: 13

DOI: 10.2174/1573405615666190903143330

Price: $65

Abstract

Background: Ultrasound (US) imaging can be a convenient and reliable substitute for magnetic resonance imaging in the investigation or screening of articular cartilage injury. However, US images suffer from two main impediments, i.e., low contrast ratio and presence of speckle noise.

Aims: A variation of anisotropic diffusion is proposed that can reduce speckle noise without compromising the image quality of the edges and other important details.

Methods: For this technique, four gradient thresholds were adopted instead of one. A new diffusivity function that preserves the edge of the resultant image is also proposed. To automatically terminate the iterative procedures, the Mean Absolute Error as its stopping criterion was implemented.

Results: Numerical results obtained by simulations unanimously indicate that the proposed method outperforms conventional speckle reduction techniques. Nevertheless, this preliminary study has been conducted based on a small number of asymptomatic subjects.

Conclusion: Future work must investigate the feasibility of this method in a large cohort and its clinical validity through testing subjects with a symptomatic cartilage injury.

Keywords: Ultrasound, osteoarthritis, anisotropic diffusion, diffusivity function, gradients, flow function, edge preservation, speckle noise.

Graphical Abstract

[1]
Nuki G. Diseases of the connective tissues, joints and bones.Davidson’s principles and practice of medicine. Edinburgh: Churchill Livingstone 1998; pp. 864-939.
[2]
Eckstein F, Flavia CJ-P. Raynauld, JC Waterton, C Peterfy. Magnetic Resonance Imaging (MRI) of articular cartilage in knee Osteoarthritis (OA): morphological assessment. Osteoarthritis Cartilage 2006; 14: 46-75.
[3]
Hossain MB, Lai KW, Pingguan-Murphy B, Hum YC, Maheza IMS, Liew YM. Contrast enhancement of ultrasound imaging of the knee joint cartilage for early detection of knee osteoarthritis Biomed Sign Process = Control. 2014; 13: 157-67.
[http://dx.doi.org/10.1016/j.bspc.2014.04.008]
[4]
Burckhardt CB. Speckle in ultrasound B-mode scans. IEEE Trans Sonics Ultrason 1978; 25(1): 1-6.
[5]
Moshe T, Chin K-C, Goodman JW. When is speckle noise multiplicative? IEEE Trans Sonics Ultrason 1978; 21(7): 1157-9.
[6]
Malik JP. Perona scale space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 1990; 12: 629-39.
[7]
Xiaoshuang M, Huanfeng S, Liangpei Z, Jie Y, Hongyan Z. Adaptive anisotropic diffusion method for polarimetric SAR speckle filtering. IEEE J-STARS 2015; 8(3): 1041-50.
[http://dx.doi.org/10.1109/JSTARS.2014.2328332]
[8]
Yu Y, Acton ST. Speckle reducing anisotropic diffusion. IEEE Trans Image Process 2002; 11(11): 1260-70.
[9]
Zhang F, Yoo YM, Koh LM, Kim Y. Nonlinear diffusion in Laplacian pyramid domain for ultrasonic speckle reduction. IEEE Trans Med Imaging 2007; 26(2): 200-11.
[http://dx.doi.org/10.1109/TMI.2006.889735]
[10]
Jian L, Bovik AC. Smoothing low-SNR molecular images via anisotropic median-diffusion. IEEE Trans Med Imaging 2002; 21(4): 377-84.
[11]
Sochen NG, Gilboa Y, Zeevi Y. Image enhancement and denoising by complex diffusion processes. IEEE Trans Pattern Anal Mach Intell 2004; 26: 1020-36.
[12]
Krissian K, Westin C-F, Kikinis R, Vosburgh KG. Oriented speckle reducing anisotropic diffusion. IEEE Trans Image Process 2007; 16(5): 1412-24.
[13]
Kuan D, Sawchuk A, Strand T, Chavel P. Adaptive restoration of images with speckle. IEEE Trans Acoust Speech Signal Process 1987; 35(3): 373-83.
[14]
Aja-Fernández S, Alberola-López C. On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering. IEEE Trans Image Process 2006; 19(5): 2694-701.
[15]
Lions P, Catte F, Morel J, Coll T. Image selective smoothing and edge detection by nonlinear diffusion. SIAM J Numer Anal 1992; 29: 182-93.
[16]
Osher S, Rudin LI. Feature-oriented image enhancement using shock filters. SIAM J Numer Anal 1990; 27(4): 919-40.
[17]
Jinhua Y, Jinglu T, Yuanyuan W. Ultrasound speckle reduction by a SUSAN-controlled anisotropic diffusion method. Patt Recogn 2010; 43(9): 3083-92.
[http://dx.doi.org/10.1016/j.patcog.2010.04.006]
[18]
Jinhua Y, Yuanyuan W, Yuzhong S. Noise reduction and edge detection via kernel anisotropic diffusion. Pattern Recognit Lett 2008; 29(10): 1496-503.
[http://dx.doi.org/10.1016/j.patrec.2008.03.002]
[19]
Reena S, Srivastava VK. Optimization of gradient threshold parameter in feature preserving anisotropic diffusion for image denoising optimization. Int J Innov Res Sci Eng Technol 2014; 3(2): 1-8.
[20]
Black MJ, Sapiro G, Marimont DH, Heeger D. Robust anisotropic diffusion. IEEE Trans Image Process 1998; 7(3): 421-32.
[21]
Xiaoping L, Tongwen C. Nonlinear diffusion with multiple edginess thresholds. Patt Recogn 1994; 27(8): 1029-37.
[http://dx.doi.org/10.1016/0031-3203(94)90142-2]
[22]
Petrou M, Petrou C. Image processing: the fundamentals. Hoboken: John Wiley & Sons 2010.
[23]
Tsiotsios C, Petrou M. On the choice of the parameters for anisotropic diffusion in image processing. Patt Recogn 2013; 46(5): 1369-81.
[24]
Zhou W, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2004; 13(4): 600-12.
[25]
Yoo YM, Zhang F, Koh LM, Kim Y. Nonlinear diffusion in Laplacian pyramid domain for ultrasonic speckle reduction. IEEE Trans Med Imaging 2007; 26: 200-11.
[26]
Wang Z, Simoncelli EP, Bovik AC. Multiscale structural similarity for image quality assessment. In: The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers Pacific Grove, . CA, USA 2003; pp. 1398-402.
[27]
Pratt WK. Digital Image Processing. New York: Wiley 1978.
[28]
Yongjian Y, Acton ST. Speckle reducing anisotropic diffusion. IEEE Trans Image Process 2002; 11(11): 1260-70.
[29]
Wang B, Garello R, Chapron B. SAR speckle characteristics observed on RADARSAT-2 dual polarization product for sea Available from:. https://pdfs.semanticscholar.org/d753/ec2fb09b1f16246f8e9c0adf56c924958719.pdf
[30]
Gagnon L, Jouan A. Speckle filtering of SAR images: a comparative study between complex-wavelet-based and standard filters. In: Proceedings of Optical Science, Engineering and Instrumentation. San Diego, CA, USA 1997; pp. 1-15.
[31]
Kamalaveni V, Rajalakshmi RA, Narayanankutty KA. Image Denoising using variations of perona-malik model with different edge stopping functions. Procedia Comput Scivol 2015; 58: 673-82.
[32]
Yu J, Zhai R, Yie J. Image denoising method based on PM model with transforming edge stopping function. In: 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC);. Chengdu, China 2017; pp. 438-2.

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