Medical Image Processing

In this Image processing project, I used a CNN classifier to classify COVID-19 Infected Lung Xray images from Healthy Lung Xray images.

Table of Contents

• DataSets
• Deep Learning Model
• Evaluation

DataSets

I selected my dataset from three different sources:

• Cohen's COVID Chest X-ray Dataset
• Paul Mooney's Chest X-ray Dataset (Pneumonia)
• COVID-19_Radiography_Dataset

Train Dataset contains 850 images by the following distribution:

Some samples of both groups:

Deep Learning Model

• Pre-trained DenseNet-121 is used as the core here for our Deep Learning Model (More details here).

• I used pre-trained weights as a means to Transfer Learning. To learn and achieve higher accuracy on our model faster.

• Instead of freezing CNN Layers and training only the Fully Connected Layer (like most people do in Classification Task), I trained all the layers, including CNNs and Classification layer.

Evaluation

Test Dataset contains 200 images from each group.

Classification results:

              precision    recall  f1-score   support

           0       0.73      0.95      0.83       200
           1       0.94      0.66      0.77       200
    accuracy                           0.81       400
   macro avg       0.84      0.80      0.80       400
weighted avg       0.84      0.81      0.80       400

Confusion Matrix:

Appendix

Many thanks to Arun Pandian R for his useful tutorial.