Fahima Aboualmagd Essawy

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

E-mail: f_essawy@yahoo.com

Website:

Research Interests: Computational Science and Engineering, Computational Engineering, Engineering

Biography

Fahima Aboualmagd Essawy is now a Professor Emeritus, Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering, Menofia University - Menofia, Egypt. (Starting from August 1 st 2009 till now) Fahima was awarded the Degree of Bachelor of Electronic Engineering in 1972 from the Faculty of Electronic Engineering, Menofia University - Menofia, Egypt. At July 31th 1977, she started working as a Demonstrator in the same faculty. Fahima had received her Master Degree in 1979 from Helwaan University, Egypt. Fahima had received her Ph.D. degree in 1989 from the Faculty of Electronic Engineering, Menofia University - Menofia, Egypt. Her field interests: Linear Automatic Control

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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