Open AccessCOVID-19 Diagnosis from CT Imaging using Imaging and Machine Analysis
Author(s) -
Gayatri A. Deochake,
Vilas S. Gaikwad
Publication year - 2021
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i9329.0710921
Subject(s) - covid-19 , pneumonia , computed tomography , medicine , medical imaging , radiology , coronavirus , intensive care medicine , virology , pathology , disease , outbreak , infectious disease (medical specialty)
Coronavirus (COVID-19) is spreading rapidly around the world and, as of October 2020, more than 1,966,000 people have been infected in more than 200 countries. Early detection of COVID-19 is essential for the provision and protection of HIV-negative people in adequate health care for patients. To do this, we developed an automated diagnostic program for COVID-19 from pneumonia (CPA) obtained from chest tomography (CT). We propose, in particular, the Noise Resilient method of machine learning that focuses on regions of lung infection while making diagnostic decisions. Note that the sizes of the infection sites between COVID-19 and CAP are not well measured, in part due to the rapid progression of COVID-19 after the onset of symptoms. Large amounts of CVID-19 CT data from hospitals have been used to evaluate our frameworks.