Edmund Adomako

Work place: University of Information Science & Technology, ―St. Paul the Apostle‖, Partizanska B.B., 6000, Ohrid, Macedonia

E-mail: edmund.adomako@cse.uist.edu.mk


Research Interests: Image Compression, Image Manipulation, Image Processing, Medical Image Computing


Edmund Adomako is a Master of Science student in the field of Communication Networks and Security at the University of Information Science and Technology (UIST) ―St. Paul the Apostle‖ – Ohrid, Republic of Macedonia. He has completed his Bachelor of Science in Information Science and Technology in the field of Computer Science and Engineering at UIST. He is currently employed at UIST as Scientific Research Advisor. His research interests are in Biomedical Imaging and Signal Processing, Linux operating system self-built from scratch and beyond, Arduino and Matlab simulation, High Performance Computer. His computer skills include C, C++, C#, ASP.NET MVC, Java, SQL, MySQL, Ajax, XML and PHP.

Author Articles
A Novel Approach to T2-Weighted MRI Filtering: The Classic-Curvature and the Signal Resilient to Interpolation Filter Masks

By Carlo Ciulla Farouk Yahaya Edmund Adomako Ustijana Rechkoska Shikoska Grace Agyapong Dimitar Veljanovski Filip A. Risteski

DOI: https://doi.org/10.5815/ijieeb.2016.01.01, Pub. Date: 8 Jan. 2016

This paper presents a novel and unreported approach developed to filter T2-weighetd Magnetic Resonance Imaging (MRI). The MRI data is fitted with a parametric bivariate cubic Lagrange polynomial, which is used as the model function to build the continuum into the discrete samples of the two-dimensional MRI images. On the basis of the aforementioned model function, the Classic-Curvature (CC) and the Signal Resilient to Interpolation (SRI) images are calculated and they are used as filter masks to convolve the two-dimensional MRI images of the pathological human brain. The pathologies are human brain tumors. The result of the convolution provides with filtered T2-weighted MRI images. It is found that filtering with the CC and the SRI provides with reliable and faithful reproduction of the human brain tumors. The validity of filtering the T2-weighted MRI for the quest of supplemental information about the tumors is also found positive.

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