COVID-19 Detection Based on Chest X-ray Images Dataset I used total 798 sample images, 399 for COVID-19 and 399 normal X-ray images.
https://algo.volganga.com/deep-learning-model-for-detecting-covid-19-on-chest-x-ray-using-matlab/
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Why X-ray (Radiography)
It usually takes less than 15 minutes for an entire X-ray procedure.
X-ray images are digital, so a doctor can see them on a screen within minutes.
We will use ResNet-50 network in this example as it has proven to be highly effective for various medical imaging applications
About ResNet-50
ResNet-50 is a convolutional neural network that is 50 layers deep.
ResNet, short for Residual Networks is a classic neural network used as a backbone for many computer vision tasks.
This model was the winner of ImageNet challenge in 2015.
You can load a pretrained version of the network trained on more than a million images.
Cite As
Link to download COVID19 Dataset https://github.com/ieee8023/covid-chestxray-dataset Link to download uninfected dataset https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia Inspired by MathWorks Blog: https://blogs.mathworks.com/deep-learning/2020/03/18/deep-learning-for-medical-imaging-covid-19-detection/
MATLAB Release Compatibility
- Compatible with R2019b and later releases
Platform Compatibility
- Windows
- macOS
- Linux
