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 Sun, 07 Jun 2020 07:20:54 +0000

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
Created with R2020a
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!