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Deep Learning Model for Detecting COVID-19 on Chest X-ray

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.

Updated 07 Jun 2020

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/

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MATLAB Release Compatibility
Created with R2020a
Compatible with R2019b to any release
Platform Compatibility
Windows macOS Linux