Mobile Framework for CT Image Reconstruction

Authors

  • M.S.M. Yusoff Institute of Visual Informatics, National University of Malaysia (UKM), 43600 Bangi, Selangor, Malaysia
  • R. Sulaiman Institute of Visual Informatics, National University of Malaysia (UKM), 43600 Bangi, Selangor, Malaysia
  • K. Shafinah Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, National University of Malaysia.
  • R. Fatihah Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, National University of Malaysia.
  • J. Abdullah Industrial Division, Malaysian Nuclear Agency, Bangi, 43000 Kajang, Selangor, Malaysia

Keywords:

Data Flow Diagram, Datasets, Sinogram, Backprojection, CT Image Reconstruction, Filter,

Abstract

Mobile devices have conquered the world from a common daily usage as e-mail to a complex application as Global Positioning System. The mobile devices have a potential to be developed as a computed device with an application to reconstruct images from computed tomography. The mobile CT application was developed to visualize the CT datasets by plotting out a test dataset to form a sinogram image on the mobile device’s screen. The image was obtained by reconstructed the CT datasets using filtered backprojection image processing algorithm. The CT datasets were filtered by using filtered datasets before the image reconstruction processes. The filtering process was a method to remove the blurring effect of the backprojection algorithm.

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Published

2017-03-15

How to Cite

Yusoff, M., Sulaiman, R., Shafinah, K., Fatihah, R., & Abdullah, J. (2017). Mobile Framework for CT Image Reconstruction. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(1-3), 119–122. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1755

Issue

Vol. 9 No. 1-3: Smart City Technology in Communication and Computer Engineering I

Section

Articles

License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)