An Analysis of COVID-19 using X-ray Image Segmentation based Graph Cut and Box Counting Fractal Dimension - Faiz Ainur Razi (Universitas Amikom Purwokerto, 2021)
COVID-19 is a disease that spreads relatively quickly. So that many victims are infected by this virus. There are various ways to diagnose the body's infection with the coronavirus. One of them with X-ray results. Detecting COVID-19 with the help of an X-ray sometimes has problems determining the location of the lesion because it is possible because of the large amount of noise in the image. Therefore, the X-ray results will be segmented images using the graph cut algorithm to analyze normal lungs and lungs infected with COVID-19. After obtaining the segmentation results in the form of binary images, the next step is to analyze using the box-counting method's fractal dimensions. From the fractal Dimension results, normal lungs have an average dimension of 1.7890, and lungs infected with COVID-19 have an average dimension of 1.5834. Normal lungs have dimensions larger than lungs infected with the coronavirus due to the lungs' covering by lesions or abnormal conditions in body tissues. This is what causes COVID-19 patients to have complaints of difficulty breathing.