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

ISSN: 2074-9074 (Print), ISSN: 2074-9082 (Online)

Published By: MECS Press

IJIGSP Vol.5, No.7, Jun. 2013

Visual Improvement for Hepatic Abscess Sonogram by Segmentation after Curvelet Denoising

Full Text (PDF, 741KB), PP.9-17

Views:94   Downloads:0


Mohammed Tarek GadAllah,Mohammed Mabrouk Sharaf,Fahima Aboualmagd Essawy,Samir Mohammed Badawy

Index Terms

Image Segmentation – Ultrasound Medical Imaging – Curvelet Transform


A wise automated method for wisely improving the visualization of hepatic abscess sonogram, a modest trial is being done to denoise and reduce the ultrasound scan speckles wisely and effectively. As an effective way for improving the diagnostic decision; improved sonogram for hepatic abscess is reconstructed by ultrasound scan image segmentation after denoising in Curvelet transform domain. Better sonogram visualization is required for better human interpretation. Speckle noise filtering of medical ultrasound images is needed for enhanced diagnosis. Double thresholding segmentation was applied on, an ultrasound scan image for a Liver with amebic abscess, after it had been denoised in Curvelet transform domain. The result is enhanced wise effect on the hepatic abscess sonogram image's visualization which improves physicians' decisions. Moreover, this method effectively reduces the memory storage size for the image which consequently decreases computation processing time.

Cite This Paper

Mohammed Tarek GadAllah,Mohammed Mabrouk Sharaf,Fahima Aboualmagd Essawy,Samir Mohammed Badawy,"Visual Improvement for Hepatic Abscess Sonogram by Segmentation after Curvelet Denoising", IJIGSP, vol.5, no.7, pp.9-17, 2013.DOI: 10.5815/ijigsp.2013.07.02


[1]Hill, C. R., Bamber, J. C., and ter Haar, G. R., "Physical principles of medical ultrasonics, 2nd edition", Ch.8: (Ultrasonic Images and the Eye of the Observer), 2004, [John Wiley, Chichester, UK]

[2]Clinical Key – Elsevier, Liver Abscess, website: abscess.html

[3]Wikipedia, Amoebic liver abscess, website:

[4]Mohamed Tarek GadAllah & Samir Badawy, "Aorta's abnormalities detection by Ultrasonography scan Denoising in Curvelet Transform Domain", Accepted, Refereed, and Presented in Al-Azhar Engineering Twelfth International Conference, Cairo, Egypt, Dec. 25-27, 2012. Published in Journal of Al-Azhar University Engineering Sector, JAUES, Vol. (7), No. (3), pp. 395 – 403, E38, Dec. 2012. EJAUES website:

[5]Mohamed Tarek GadAllah & Samir Badawy, "Diagnosis of Fetal Heart Congenital Anomalies by Ultrasound Echocardiography Image Segmentation after Denoising in Curvelet Transform Domain", Refereed, Accepted, and Presented in The 2012 World Congress on Electronics and Electrical Engineering [WCEEENG'12], Cairo, Egypt, Dec. 23 - 27, 2012, Published in the Online Journal on Electronics and Electrical Engineering (OJEEE), ISSN (2090-0279), Vol. (5), No. (2), pp. 554 - 560, Reference No. : W13-E-0023, April 2013. Online Paper Location:

[6]F. Yousefi Rizi, S. K. Setarehdan, "Noise Reduction in Intravascular Ultrasound Images Using Curvelet Transform and Adaptive Complex Diffusion Filter: a Comparative Study", 20th Iranian Conference on Electrical Engineering, (ICEE2012), Tehran, Iran, May 15-17, 2012

[7]Hassen LAZRAG, Med Ali HAMDI, and Med Saber NACEUR, "Despeckling of Intravascular Ultrasound Images using Curvelet Transform", SETIT 2012 Sciences of Electronics, Technologies of Information and Telecommunication, March 2012.

[8]F. Yousefi Rizi, H. Ahmadi Noubari, and S. K. Setarehdan, "Wavelet-Based Ultrasound Image Denoising: Performance Analysis and Comparison", 33rd Annual International Conference of the IEEE EMBS. Boston, Massachusetts USA, August 30 - September 3, 2011.

[9]Aliaa A. A. Youssif, A. A. Darwish, and A. M. M. Madbouly, "Adaptive Algorithm for Image Denoising Based on Curvelet Threshold", IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.1, January 2010.

[10]Anil A Patil and Jyoti Singhai, "Image denoising using curvelet transform: an approach for edge preservation", Journal of Scientific & Industrial Research, Vol. 69, pp. 34-38, January 2010.

[11]H. Rabbani, Student Member, IEEE, M. Vafadust, and S. Gazor, Senior Member, IEEE, "Image Denoising in Curvelet Transform Domain Using Gaussian Mixture Model with Local Parameters for Distribution of Noise Free Coefficients", Proceedings of the 4th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors St Catharine's College, Cambridge, UK, Aug. 19-22, 2007.

[12]Nguyen Thanh Binh and Nguyen Chi Thanh, " OBJECT DETECTION OF SPECKLE IMAGE BASE ON CURVELET TRANSFORM", ARPN Journal of Engineering and Applied Sciences, ISSN 1819-6608, VOL. 2, NO. 3, JUNE 2007.

[13]Jean-Luc Starck, Emmanuel J. Candès, and David L. Donoho, "The Curvelet Transform for Image Denoising", IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 11, NO. 6, JUNE 2002.

[14]Alasdair McAndrew, "An Introduction to Digital Image Processing with Matlab Notes for SCM2511 Image Processing 1", School of Computer Science and Mathematics Victoria University of Technology, Semester 1, 2004.

[15]SANDEEP PALAKKAL, "Ridgelet and Curvelet first generation Toolbox", 25 May 2011 (Updated 21 Mar 2012).

[16]Emmanuel J. Candµes and David L. Donoho, "Curvelets - A Surprisingly Effective Nonadaptive Representation For Objects with Edges", Saint-Malo Proceedings, Vanderbilt University Press, Nashville, TN, 1999.

[17]David L. Donoho & Mark R. Duncan, "Digital Curvelet Transform: Strategy, Implementation and Experiments", Department of Statistics Stanford University, November, 1999.

[18]Mohamed Elhabiby, Ahmed Elsharkawy, and Naser El-Sheimy, "Second Generation Curvelet Transforms Vs Wavelet transforms and Canny Edge Detector for Edge Detection from WorldView-2 data", International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.4, August 2012

[19]Ultrasound image gallery, A free gallery of high-resolution, ultrasound, color Doppler and 3D images, Liver, "Hepatic abscess or abscess of Liver (Amebic liver abscess)", website:

[20]Ultrasound image gallery, A free gallery of high-resolution, ultrasound, color Doppler and 3D images, Fetal-heart, "Normal four chamber view of the fetal heart", website: