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CNN-COVID-19-classification-using-chest-CT-scan

COVID-19 classification based on chest CT scan using convolutional neural network

Description

There are two Jupyter notebooks in this repo (in notebooks folder).

1. 1-Introduction-to-convolutional-neural-network
   • This notebook introduces deep neural network (DNN) and convolutional neural network (CNN) to those who are not familiar with this area.
   • I illustrate the key components in a DNN, motivation for CNN and features that make CNN powerful for image classification.
2. 2-COVID-19-classification-based-on-CT-scan
   • This notebook is a walk-through of a CNN COVID-19 CT scan classifier that we’ve built using tensorflow.keras.
   • We built the network as an entry to the INFORMS QSR data challenge.

Team members who built the COVID classifier: A/P Chen Nan, Shi Yuchen, and me.

The CT scan data set is from here. Their details are described in this preprint: COVID-CT-Dataset: A CT Scan Dataset about COVID-19.

Set up

1. Clone the repository

You can do so by executing the following in your terminal:

git clone https://github.com/YangXiaozhou/CNN-COVID-19-classification-using-chest-CT-scan

Alternatively, you can download the zip file of the repository at the top of the main page of the repository.

2. Download Anaconda (if you haven’t already)

If you do not already have the Anaconda distribution of Python 3, go get it (You can also do this without Anaconda: using pip to install the required packages, however Anaconda is great for Data Science and I encourage you to use it).

3. Create a new conda environment

Navigate to the relevant directory in your terminalCNN-COVID-19-classification-using-chest-CT-scan and install required packages in a new conda environment:

conda env create -f environment.yml

This will create a new environment called CNN-COVID-19-classification-using-chest-CT-scan. To activate the environment on OSX/Linux, execute

source activate CNN-COVID-19-classification-using-chest-CT-scan

On Windows, execute

activate CNN-COVID-19-classification-using-chest-CT-scan

4. Open your Jupyter notebook

In the terminal, execute jupyter notebook.

Then open the notebook 1-Introduction-to-convolutional-neural-network.ipynb and you’re ready to dive in. Enjoy.