Open AccessEffective Survey on Detection and Classification of COVID-19 Suspected Individual Using CT scan Images
Author(s) -
Snehal R. Sambhe,
Kamlesh A. Waghmare
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit217339
Subject(s) - covid-19 , extractor , artificial intelligence , computer science , quarantine , coronavirus , medicine , feature (linguistics) , test (biology) , computed tomography , radiology , medical physics , pattern recognition (psychology) , virology , pathology , disease , engineering , biology , infectious disease (medical specialty) , paleontology , linguistics , philosophy , process engineering , outbreak
As insufficient testing kits are available, the development of new testing kits for detecting COVID remains an open vicinity of research. It’s impossible to test each and every patient suffering from coronavirus symptoms using the traditional method i.e. RT-PCR. This test requires more time to produce results and have less sensitivity. Detecting feasible coronavirus infection using chest X-Ray may also assist quarantine excessive risk sufferers while testing results are disclosed. A learning model can be built based on CT scan images or Chest X-rays of individuals with higher accuracy. This paper represents a computer-aided diagnosis of COVID 19 infection bases on a feature extractor by using CNN models.