https://github.com/pottekkat/covid-detection-using-chest-x-rays
CNN model that would detect COVID-19 from Chest X-ray images, and after training the model with 251 images, the model yielded 99%+ accuracy.
https://github.com/pottekkat/covid-detection-using-chest-x-rays
Last synced: 2 months ago
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CNN model that would detect COVID-19 from Chest X-ray images, and after training the model with 251 images, the model yielded 99%+ accuracy.
- Host: GitHub
- URL: https://github.com/pottekkat/covid-detection-using-chest-x-rays
- Owner: pottekkat
- Created: 2020-05-16T16:34:58.000Z (almost 5 years ago)
- Default Branch: master
- Last Pushed: 2020-05-16T16:36:58.000Z (almost 5 years ago)
- Last Synced: 2025-01-07T15:29:24.950Z (4 months ago)
- Language: Jupyter Notebook
- Size: 383 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Detecting COVID-19 infection using Chest X-rays
The exponential increase in COVID-19 patients is overwhelming the healthcare systems across the world and it continues to have a devastating effect on the population. A critical step in the fight against the virus is a fast and reliable testing technique. The conventional techniques (RT-PCR) is costly and more importantly they take time and have limited sensitivity.
While the diagnosis is confirmed using polymerase chain reaction (PCR), infected patients with pneumonia may present on chest X-ray and computed tomography (CT) images with a pattern that is only moderately characteristic for the human eye. In late January, a Chinese team published a paper detailing the clinical and paraclinical features of COVID-19. They reported that patients present abnormalities in chest CT images with most having bilateral involvement.
Detecting possible COVID-19 infection from Chest X-ray will provide a faster and reliable method that could be used with the conventional tests for faster detection. Since most modern healthcare systems are equipped with digitized X-ray machines, there are no additional costs or resources required for testing.
The system used consists of a model which has been trained on 250+ Chest X-ray images. The model uses computer vision techniques to determine the anomalies in the images and determines whether the patient has been infected with COVID-19. Most of this anomalies are invisible to the naked eye as shown below.
The model when tested showed an accuracy of 99%. i.e the model can effectively predict if a person is affected by COVID-19 with Chest X-rays with almost 100% certainty.