Abstract
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.
Highlights
Corona Virus Disease 2019 or COVID-19 is a virus that emerged at the end of 2019
The X-ray results will be segmented images using the graph cut algorithm to analyze normal lungs and lungs infected with COVID-19
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
Summary
Corona Virus Disease 2019 or COVID-19 is a virus that emerged at the end of 2019. This virus first broke out in Wuhan City, China. This study will use the role of fractal geometry to analyze infections that occur in the lungs due to COVID-19. There is a discussion of fractal dimensions in fractal geometry, which has an important role in analyzing complex objects (Cimen et al, 2021; Nayak et al, 2019) This method is useful for analyzing a disease in the medical world when the Euclidian geometry cannot be used to complete an image analysis. One of the roles of fractal geometry used to analyze image segmentation results is by using the boxcounting method. This algorithm uses the fractal dimensions' calculated square measure to determine the number of cubes needed to cover the totality. The image that has been segmented is analyzed using the box counting method's fractal geometry. Dimension is 1.6471, with the selection of many boxes covering the object is 256 boxes
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