Madan Lal; Lakhwinder Kaur; Savita Gupta

Speckle Reduction with Edge Preservation in B-Scan Breast Ultrasound Images

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Author(s)

Madan Lal ^1,* Lakhwinder Kaur ¹ Savita Gupta ²

1. Department of Computer Engineering, Punjabi University, Patiala. India.

2. Department of Computer Science & Engineering, Punjab University, Chandigarh. India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2016.09.08

Received: 27 May 2016 / Revised: 6 Jul. 2016 / Accepted: 10 Aug. 2016 / Published: 8 Sep. 2016

Index Terms

Speckle Noise, Smoothing, Edge preservation, Breast Ultrasound (BUS) image

Abstract

Speckle is a multiplicative noise that degrades the quality of ultrasound images and its presence makes the visual inspection difficult. In addition, it limits the professional application of image processing techniques such as automatic lesion segmentation. So speckle reduction is an essential step before further processing of ultrasonic images. Numerous techniques have been developed to preserve the edges while reducing speckle noise, but these filters avoid smoothing near the edges to preserve fine details. The objective of this work is to suggest a new technique that enhances B-Scan breast ultrasound images by increasing the speckle reduction capability of an edge sensitive filter. In the proposed technique a local statics based filter is applied in the non homogeneous regions, to the output of an edge preserving filter and an edge map is used to retain the original edges. Experiments are conducted using synthetic test image and real time ultrasound images. The effectiveness of the proposed technique is evaluated qualitatively by experts and quantitatively in terms of various quality metrics. Results indicate that proposed method can reduce more noise and simultaneously preserve important diagnostic edge information in breast ultrasound images.

Cite This Paper

Madan Lal, Lakhwinder Kaur, Savita Gupta,"Speckle Reduction with Edge Preservation in B-Scan Breast Ultrasound Images", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.8, No.9, pp.60-68, 2016. DOI: 10.5815/ijigsp.2016.09.08

Reference

[1]Cancer facts and figures by American Cancer Society (2016).

[2]R. Shivaramakrishna, R. Gordan, "Detection of breast cancer at smaller size can reduce the likelihood of metastatic spread: A quantitative analysis", Acad. Radiology. Vol.4 (1), pp. 8-12,1997.

[3]R.G. Dantas, E.T. Costa, S. Leeman, "Ultrasound speckle and equivalent scatterers", J. Ultrasonic. Vol. 43, pp. 405–420, 2005.

[4]Gonzalez RC, Woods RE. Digital Image Processing. 3rd edition , Pearson Education Ins, 2008.

[5]J.S. Lee, "Refined filtering of image noise using local statistics," Comput. Graphics Image Process, vol. 15, pp. 380–389, 1981.

[6]Lee JS. "Speckle analysis and smoothing of synthetic aperture radar images". Computer Graphics, Image Processing; Vol.17:,pp.24-32,1981.

[7]Kuan DT, Sawchuk AA, Strand TC, and Chavel P. "Adaptive restoration of images with speckle". IEEE Transactions on Acoustics, Speech and Signal Processing Vol.35 (3), pp. 373-383, 1987.

[8]Frost VS, Stiles JA, Shanmuggam KS, and Holtzman JC. "A model for radar images and its application for adaptive digital filtering of multiplicative noise". IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol.4 (2), pp. 157-165,1982.

[9]Perona P, Malik J. , "Scale-space and edge detection using anisotropic diffusion." IEEE Transactions on Pattern Analysis and Machine Intelligence.Vol.12 (7), pp. 629-639, 1990.

[10]Y. Yongjian, S.T. Acton, "Speckle reducing anisotropic diffusion", IEEE Trans.Image Processing. Vol. 11 (11) pp. 1260–1270,2002.

[11]S. Gupta, L. Kaur, R. C. Chauhan, and S. C. Saxena, "A versatile technique for visual enhancement of medical ultrasound image," Journal of Digital Signal Processing, Elsevier, vol. 17, pp. 542-560, January 2007.

[12]A. Dixit, P. Sharma, "A Comparative Study of Wavelet Thresholding for Image Denoising", I.J. Image, Graphics and Signal Processing, Vol.46, pp.39-46,2014.

[13]A. Pizurica, A.M. Wink, E. Vansteenkiste, W. Philips, J. Roerdink, "A review of wavelet denoising in MRI and ultrasound brain imaging", Current Medical Imaging Reviews. Vol. 2 (2), pp. 247–260,2006.

[14]M. A. Gungor, I. Karagoz, "The homogeneity map method for speckle reduction in diagnostic ultrasound images", Vol.68, pp. 100-110, 2015.

[15]P.Coupe, P.Hellier, C.Kervrann, C.Barrilot, "Non local means speckle filtering for speckle reduction", IEEE transactions on speckle filtering, Vol.18, pp.2221-2229, 2009.

[16]A. Pizurika, W. Philips, I. Lemahieu, M. Acheroy, "A versatile wavelet domain noise filtration technique for medical imaging", IEEE Transaction on medical imaging. Vol 22, No 03, 2003.

[17]M Lal, L. Kaur, "Comparative analysis of B-Mode Breast Ultrasound Image Enhancement Techniques", International Journal of Computer Applications.Vol.131 (17), pp. 36-40. 2015.

[18]Cristina Stolojescu-Crisan, "A Comparison of Speckle Reduction Techniques in Medical Ultrasound Imaging". Applied Medical Informatics, Vol.36 (2), pp. 43-50, 2015

[19]M. Lal, L.Kaur, "Automatic seed point selection in B-Mode breast ultrasound images", presented at 50th golden jubilee annual convention organized by Computer Society of India. 02-05 December, 2015.

[20]C.P. Loizou, C.S. Pattichis, C.I. Christodoulou, R.S.H. Istepanian, M. Pantziaris, and A. Nicolaides "Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery," IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 52, no. 10, pp. 1653–1669, 2005.

[21]B.K.Singh,K.Verma,A.S.Thoke, "Objective and Optical Evaluation of Despeckle Filters in Breast Ultrasound Images", IETE Technical review,Vol.32 No.5 pp.1-15.2015.

[22]A. A. Mahmoud, S. EL Rabaie, T. E. Taha, O. Zahran, F. E. Abd El-Samie, "Comparative Study of Different Denoising Filters for Speckle Noise Reduction in Ultrasonic B-Mode Images", I.J. Image, Graphics and Signal Processing. Vol.2, pp.1-8,2013.

[23]D.T. Kuan, A.A. Sawchuk, T.C. Strand, and P. Chavel, "Adaptive restoration of images with speckle," IEEE Trans. Acoust., vol. 35, pp. 373–383, 1987.

[24]Black M, Sapiro G, Marimont D, Heeger D. Robust anisotropic diffusion. IEEE Transactions on Image Processing .vol.7(3), pp.421-432,1998.

[25]D. Poobathy, R. Manicka Chezian, "Edge Detection Operators: Peak Signal to Noise Ratio Based Comparison", I.J. Image, Graphics and Signal Processing.Vol.10.pp-55-61,2014.

[26]Ultrasound Cases Information, http://www.ultrasoundcases.info/

[27]Ultrasound Images, http://www.ultrasound-images.com/breast.htm

[28]http://telin.ugent.be/~sanja/.

International Journal of Image, Graphics and Signal Processing (IJIGSP)