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.
In this paper, a Graphical User Interface (GUI) for Extreme Level Eliminating Adaptive Histogram Equalization (ELEAHE) is developed in this paper. This new developed GUI is used to visualize and emphasize the hypo-dense area in Computed Tomography (CT) brain images by applying ELEAHE. In the GUI, the original image and the processed image are displayed side by side when the CT images of brain are loaded. Window center and window width setting is set to default values and both of them are adjustable. Besides that, expert diagnoses on the locations of brain lesions are also provided and marked for each brain images for reference purpose. This developed GUI shows great potential to improve the manual examination and analysis of CT brain images by connecting the user with image processing algorithm. The developed application is suggested as a practical education application for medical students and fresh medical doctors in brain lesions analysis using CT images.
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