Samir Mohammed Badawy

Work place: Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menofia University, Menofia, Egypt

E-mail: drsamirb@gmail.com

Website:

Research Interests: Physics, Medical Image Computing, Image Processing, Medical Informatics

Biography

Samir Mohammed Badawy is now a Professor Emeritus, Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menofia University - Menofia, Egypt. Samir had received his Ph.D. degree from Institute of cancer research, Royal Marsden Hospital, London University, UK. Samir had received his Master Degree from Helwaan University, Egypt. He was awarded the Degree of Bachelor of Engineering from Industrial Electronics Department, Faculty of Engineering, Menofia University - Menofia, Egypt His previous and current researches interests include: Biomedical Physics, Biomedical Electronic, BCI, ECI, Medical Image Processing, Enhancement and Analysis, Ultrasound Tissue Characterization and Reconstruction, and biological Magnetic Effects on living cells.

Author Articles
Visual Improvement for Hepatic Abscess Sonogram by Segmentation after Curvelet Denoising

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

DOI: https://doi.org/10.5815/ijigsp.2013.07.02, Pub. Date: 8 Jun. 2013

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.

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