| Autor: |
Sathananthavathi, V., Juliet, R. Jenifer, Haritha, G. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 3/27/2024, Vol. 2966 Issue 1, p1-8, 8p |
| Abstrakt: |
Covid-19 is a deadly disease that has spread all over the world. It has a larger social influence. There are various ways for diagnosing the virus, including RTPCR, Xray, and others, but chest computed tomography(CT) is one of the most effective. CT images are employed to identify if there any abnormalities and level of abnormalities identification of abnormalities in CT images is highly challenging. This paper focuses on the classification of CT images into normal or abnormal and also to localize the lesions in the CT images. Here lung lesion localization for accurate screening of covid 19 in CT images is proposed by incorporating transfer learning and K-mean clustering. The proposed approach is based on Resnet 50 architecture followed by dense network for classification [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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