EFFECTIVENESS EDGE DETECTION OPERATOR CANNY TO IMPROVE IMAGE QUALITY THORAX CT SCAN IN CASES COVID-19

Background: Thorax CT scan is one of the medical supports that contributes most importantly to the diagnosis, especially cases of COVID-19. The disadvantage that has a CT scan image is noise. When the noise is high then the Signal Noise Ratio (SNR) value produced is low. Canny operator edge detection technique is one solution to animate noise. Purpose: Analyzing differences in image quality and anatomical information on thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection techniques. Method: A quasi experimental research on thorax CT Scan images before and after the application of canny operator edge detection which amounted to 10 samples. Image assessment is done by measuring noise, SNR, and anatomical information. Differences in image quality (noise and SNR) are tested with paired T-tests. Anatomical information is tested with the Wilcoxon Signed Rank Test. Result: There are differences in image quality in thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection techniques, with p-value <0.001. There are differences in the anatomical information of thorax CT scan images in COVID-19 patients before and after the application of canny operator edge detection technique with a p-value of 0.004. Conclusion: Edge detection operator canny techniques are able to lower noise values, improve SNR and improve image anatomy information thorax CT scan in COVID-19 patients.