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Deep features and radiomics selection with NSGA-II for pulmonary nodule classification

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Description

This is the second project of the Bioinspired Optimization class given by Professor Erick Barboza, PhD.

Students:

See the presentation

See a summary of the work on the Presentation

How to set up the environment for the first time

Install pip and virtualenv:

sudo apt-get install python3-pip

sudo pip3 install virtualenv

Clone the repository:

git clone [email protected]:anthonyjatoba/deep_radiomics.git

Create a virtual environment within the project directory:

cd deep_radiomics

virtualenv -p python3 env

Install the required dependencies:

source env/bin/activate

pip install -r requirements.txt

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Deep features and radiomics selection with NSGA-II for pulmonary nodule classification

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