Abstract—A graphical user interface (GUI) is developed for early infarcts detection using non-contrast brain computed tomography images. This newly developed GUI is used to train medical practitioners to detect early infarcts within the golden hours (1 to 3 hours). A number of early infarct cases are selected randomly without repetition from the stand-alone database, and brain DICOM images of each selected case are displayed. The user is given a time limit to diagnose the early infarcts locations, with the assistance of windowing technique, colorization method, and 3D modeling method that can enhance the CT images. The performance of the practitioner is determined from the time taken and the marks obtained, after comparing the practitioner’s answer with the expert diagnosis.
Index Terms—Training system, early infarcts, window settings, colorization.
The authors are with the Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama Bukit Beruang 75450 Melaka, Malaysia (e-mail: casionee90@gmail.com, realize_bibi@hotmail.com, kssim@mmu.edu.my, cptso@mmu.edu.my).
[PDF]
Cite: Chung Sheng Ee, Fung Fung Ting, Kok Swee Sim, and Chih Ping Tso, "Development of a Graphical User Interface Training System for Early Infarct Detection," International Journal of Information and Electronics Engineering vol. 6, no. 1, pp. 54-58, 2016.
