zeyadusf / chest_xray_classification

Chest X-Ray Classification - CNN

Chest X-ray Pneumonia Classification

🎯 About

In this project, we develop a convolutional neural network (CNN) model for classifying chest X-rays as either normal or showing signs of pneumonia. The model was trained on a dataset of over 5,863 X-ray images, and achieved an accuracy of 89% on the test set. The architecture of the model consists of multiple convolutional layers, followed by max pooling and dense layers.

dataset we used Chest X-Ray Images (Pneumonia)

full project in details in the documentation

✨ Features

✔️Classify the x-ray imagest to two category

• Pneumonia
• Normal

✔️Used All evaluation metrics

🚀 Technologies

The following tools were used in this project:

• tensorflow==2.12.0
• tqdm
• scikit-learn
• matplotlib
• numpy
• pandas
• pickle
• cv2
• CNN
• Tensorflow, keras
• Jupyter notebook
• deep learning

👥 collaborators

• Romani     

• Ahmed Mohamed Ali             

• Reham Mustafa            

• Sara Reda Moatamed

• Rana Hasan Badrawy

• Rawan Abdel-Aziz Ahmed    

  ---

📧 Contact