Automatic COVID-19 Lung Infection Segmentation CT Image

Abstract

From last two years Covid-19 become a critical pandemic over the world. This corona virus
impacts the billions of peoples over the world. This covid-19 is the cause of some disease
like heart problems, Lungs complications, pneumonia, liver problems and respiratory failure.
Computer Tomography (CT) is the best strategy is used to detect lungs infection due to
Covid-19. The covid-19 Virus impacts the human lungs and other critical organ of human
body. The virus of Covid-19 spread human to human contact it spread by the droplets which
comes from person’s mouth when person will coughs exhales or sneezes. As these droplets
are too heavy then it can’t stay in the air then these droplets fall on floor or surface. These
droplets contain covid-19 virus. Now everyone aware about the health crisis came in the
world because of covid-19 virus. For this time automatic detection of lung infection from CT
image plays an important role. But it has main challenge of segmenting infected region from
CT slices, which include closeness in the gray level and low intensity that helps differentiate
between infections and conventional tissues. The most objective is the make an programmed
apparatus for Covid-19 contamination division utilizing the chest CT image. We collected a
huge amount of data of CT images of covid-19 affected patients. Our purpose of solution that
analyze the person lungs CT image and find the infected part of lung and also detect the
affected part percentage. This system will help the patients to take essential measures.