Department of E&CE, Angadi Institute of Technology and Management Belagavi, India
Abstract
The corona virus disease is an infectious disease which primarily affects lungs of human body. Medical imaging using computed tomography (CT) plays an important role in the global fight in COVID-19. In present days deep learning techniques is useful for diagnose lung affected by covid-19 patients. HRCT images provide good analysis of segmentation of CT images. This process is based on segmentation of medical images in line with convolution neural networks which utilizes augmentation of data, evaluation pre-processing and segmentation of image analysis. Using u-net architecture this paper highlights an approach for lunch images of CT segmentation. The result shoes a comparative lung image of covid-19 patient and non covid-19 patient using U-net Architecture lung augmentation.
Jadhav, A., & Pujari, S. (2021). Segmentation And Analysis Of Covid-19 Chest Ct Scan Images Using The Methods Of Deep Learning. Int. J. of Aquatic Science, 12(3), 2786-2793.
MLA
Aravind Jadhav; Sanjay Pujari. "Segmentation And Analysis Of Covid-19 Chest Ct Scan Images Using The Methods Of Deep Learning". Int. J. of Aquatic Science, 12, 3, 2021, 2786-2793.
HARVARD
Jadhav, A., Pujari, S. (2021). 'Segmentation And Analysis Of Covid-19 Chest Ct Scan Images Using The Methods Of Deep Learning', Int. J. of Aquatic Science, 12(3), pp. 2786-2793.
VANCOUVER
Jadhav, A., Pujari, S. Segmentation And Analysis Of Covid-19 Chest Ct Scan Images Using The Methods Of Deep Learning. Int. J. of Aquatic Science, 2021; 12(3): 2786-2793.
)