Pneumonia Image Classification based on Convolutional Neural Network
Date:
- Developed an CNN model aimed at classifying pneumonia pathogens using patients’ chest CT images.
- Treated 18,000 chest CT scans from patients with COVID-19, SARS, and bacteria infected.
- Constructed a model of 3 convolutional layers and 3 max-pooling layers.
- Performed gradient comparison analysis to define the optimal parameter of each layer.
- Achieved a training accuracy of 97.9% and a testing accuracy of 91.8%.
- Scored 90 and was awarded “Distinction” in project evaluation (the highest level attainable).