HYBRID TECHNIQUES FOR THE SEGMENTATION INFECTION WITH COVID-19 IN THE LUNGS USING CT IMAGES

COVID-19 is a deadly disease which causes infection in both animals and human beings. It is a
zoonotic disease that scatters worldwide in the beginning of the year 2020. COVID- 19 is termed as
Corona Virus Infection in 2019that makes the whole world to suffer from this existential infection.
The Chest x-rays detect lung pollution automatically. Images from computed tomography that aid
in the struggle against COVID-19. Several demands are created during the separation of the
diseased component from the X-ray slices, including a large difference in disease characteristic and
a low intensity difference betweeninfected and normal tissues. The deep model's pedagogy makes it
hard to gather a large amount of a large amount of data in a short period of time. For Addressing
the separation of COVID- 19 related lung disease by using Seg-Net It is proposed that the damaged
areasof the chest X-ray be automatically analysed scan, using image process technique to automate
the operation to increase the efficiency of the system.