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DC Field | Value | Language |
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dc.contributor.author | HIMANSHU RAJ | - |
dc.date.accessioned | 2022-02-21T08:29:05Z | - |
dc.date.available | 2022-02-21T08:29:05Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://dspace.dtu.ac.in:8080/jspui/handle/repository/18814 | - |
dc.description.abstract | COVID-19 cases are increasing worldwide day by day leads to a huge load on health amenities. Due to the limited accessibility of reverse transcription-polymerase chain reaction (RT-PCR) kits, every patient with respiratory illness could not get tested by it. The tests are time-consuming, and they have limited sensitivity x-ray for the detection of covid-19 in patients. Meanwhile using an x-ray machine is a more feasible, available, and economical option. For the same reason, we consider x-ray images for our research purpose. We implemented the CNN model on the image dataset of the x-ray of the patient and successfully achieved an accuracy of 96%. Sometimes RT-PCR is a false negative in such a situation it would be helpful and avoid RT-PCR. By using modern AI techniques, the x-ray images of covid-19 patients in an automated manner can be used to diagnose at the settings where trained radiologists are not available. | en_US |
dc.language.iso | en | en_US |
dc.publisher | DELHI TECHNOLOGICAL UNIVERSITY | en_US |
dc.relation.ispartofseries | TD - 5344; | - |
dc.subject | CHEST X-RAY IMAGE | en_US |
dc.subject | RT-PCR | en_US |
dc.subject | CNN MODEL | en_US |
dc.subject | TRANSCRIPTION-POLYMERASE | en_US |
dc.title | A FRAMEWORK OF CONVONET FOR DETECTION OF COVID-19 IN CHEST X-RAY IMAGE | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | M.E./M.Tech. Information Technology |
Files in This Item:
File | Description | Size | Format | |
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Thesis.pdf | 1.17 MB | Adobe PDF | View/Open |
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